• Journal of the Korean Society for Precision Engineering
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• v.31 no.7
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• pp.627-634
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• 2014

Machine tool vibration is well known for reducing machining accuracy. Because vibration response of a linear structure generally depends on its transfer function if the magnitude of excitation were kept constant, this study introduces a RET(Random Excitation Test) based on FRF method to evaluate stiffness of a prototype HDMTL(Heavy-Duty Multi-Tasking Lathe) for large crankshaft of marine engine. Firstly, two force loops of the lathe and corresponding structural loops were identified:1) workpiece - spindle - head stock - main bed, 2) workpiece - tool post - carriage bed. Secondly, compliances of each structural loop were measured respectively using RET with a hydraulic exciter and then converted into stiffness. Finally, the measured stiffness was compared with that obtained previously by FEM analysis. As the result, both measured and computed stiffness were closely in agreement with each other. And the prototype HDMTL has evidently sufficient rigidity above ordinary heavy-duty lathes.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.19 no.12
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• pp.1260-1268
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• 2009

Three methods(the stepped sine method, the statistical method(random excitation method) and the maximum-length sequence(MLS) method) for head-related transfer functions(HRTFs) are experimentally compared in view point of accuracy and efficiency. First, the stepped sine method has high signal-to-noise ratio, but low efficiency. Second, the statistical method is fast measurement speed, but weak to noise than the other methods. Finally, the MLS method shows both good efficiency and high signal-to-noise ratio, but it needs additional software or equipment such as MLS signal generator. For comparison of measurement accuracy, HRTFs of KEMAR dummy are measured for various azimuths and elevations. Error norms for magnitude and phase of HRTFs are defined and calculated for the measured HRTFs. The calculated error norms show that the methods give similar results in magnitude and phase except a little phase difference in the MLS method.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.33 no.5
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• pp.41-49
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• 2005

This paper discusses the test procedure, instrumentation, verification methodology and the results of the ground vibration test(GVT) performed on the KF-16D aircraft to estimate experimentally dynamic characteristics of the aircraft. The modal tests for 7 external store configurations were conducted to estimate effects of external stores on the aircraft vibration modes. To emulate free-free boundary conditions the test aircraft was mounted on its landing gear structure with deflated tires during the GVT. The airframe modal tests were done by burst random excitations with 6 to 8 shakers and about 200 accelerometers. Frequency response functions(FRFs) were measured for each test, and the FRFs were reduced and analyzed to identify the dynamic parameters interested. The analyses were carried out in two steps. To extract modal parameters such as, frequencies and damping ratios, the poly-reference least square complex exponential method was used in the time domain. The mode shape coefficients were estimated with the least squares frequency domain method to identify the vibration modes.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.38 no.5
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• pp.482-489
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• 2010

This paper describes the test procedure, instrumentation, verification methodology and the results of the ground vibration test(GVT) and force vibration test(FVT) of the SmartUAV aircraft to estimate experimentally dynamic characteristics of the aircraft. Bungee cords are used to emulate free-free boundary conditions of the test aircraft. The SmartUAV is excited by three shakers and one-hundred frequency response functions(FRF's) is measured. The FRF's are reduced and analyzed to identify the dynamics parameters of the SmartUAV. To extract modal parameters of the SmartUAV such as, natural frequencies and damping ratios, the poly-reference least square complex exponential method is used in the time domain. The mode shape coefficients are estimated with the least squares frequency domain method to identify the vibration modes. The FVT was performed by fixed sine frequency with three shakers on the x, y and z direction and vibration characteristics of structures and detail equipments are measured.

• Journal of the Institute of Convergence Signal Processing
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• v.25 no.2
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• pp.119-126
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• 2024

This study aims to evaluate the feasibility of an early warning system for college dropout by machine learning the main patterns that affect college student dropout and to suggest ways to implement a system that can actively prevent it. For this purpose, a performance comparison experiment was conducted using five types of machine learning-based algorithms using data from the Korean Educational Longitudinal Study, 2005, conducted by the Korea Educational Development Institute. As a result of the experiment, the identification accuracy rate of students with the intention to drop out was up to 94.0% when using Random Forest, and the recall rate of students with the intention of dropping out was up to 77.0% when using Logistic Regression. It was measured. Lastly, based on the highest prediction model, we will provide counseling and management to students who are likely to drop out, and in particular, we will apply factors showing high importance by characteristic to the counseling method model. This study seeks to implement a model using IT technology to solve the career problems faced by college students, as dropout causes great costs to universities and individuals.

• Proceedings of the KIEE Conference
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• 2000.07a
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• pp.55-57
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• 2000

대규모의 전력을 사용하며 전력 수요가 일정하지 않고 변동하는 제철소의 전기아크로 (electric arc furnace) 부하는 전압 플릭커 (voltage flicker) 등 전력품질을 저하시키는 현상의 주 원인이 되고 있다. 따라서, 전력품질의 향상을 위한 전력계통의 계획과 운용에 있어서 이러한 부하들의 비선형적인 전압-전류 특성을 해석하고 모델링하는 것이 우선 되어야 한다. 특히 전기아크로 부하의 비선형적이고 랜덤 신호에 가까운 특성은 stochastic 접근법에 의해 주로 모델링되어 왔으나, 전기아크로 부하에 의한 전력계통에서의 영향을 평가를 위해서는 deterministic 접근법에 의한 모델링이 필요하며 전기아크로 부하가 가지는 chaos 특성을 Lorenz 시스템으로 표현한 부하모델이 개발되었다[1]. 개발된 모델에 의해 하나의 chaos 시스템으로 예측된 전기아크로 부하 패턴은 전 동작 범위에서 부하 특성을 정확하게 반영하는데 문제가 있다. 따라서, 전기아크로 부하 패턴을 표현할 수 있는 복수의 chaos 시스템을 이용하여 보다 나은 예측 특성을 가진 부하 모델의 개발이 필요하다. 본 논문에서는 기존의 Lorenz 시스템과 전기아크로 부하의 고주파영역 특성을 보다 적절하게 반영할 수 있는 Logistic 시스템을 혼합한 형태의 chaos 모델을 개발하고, 전력 계통에서의 전력품질 저하현상을 정량화하는 지수를 통해 모델의 유용성과 정확성을 검증하고자 한다.

• Journal of the Korea Institute of Military Science and Technology
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• v.2 no.1
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• pp.30-37
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• 1999

Transmissivity and the signal loss in soil are computed. An electric field expression for the inhomogeneous complex media modelled by two layers is shown as an integral form. Volume scattering occurs in inhomogeneous media, and iterative Born approximation is used to analyze this scattering effect. The degree of randomness is controlled by specifying the variance and correlation length. Expression for the transmissivity and the signal loss is presented as the parameter of soil moisture contents, soil particle radius, temperature and frequency. The analysis shows that big deviation in signal loss depends on the temperature variation remarkably and the physical reason of unusual level is explained.

• The Korean Journal of Applied Statistics
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• v.29 no.7
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• pp.1311-1327
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• 2016

We propose a multi-state model for analyzing semi-competing risks data with interval-censored or missing intermediate events. This model is an extension of the 'illness-death model', which composes three states, such as 'healthy', 'diseased', and 'dead'. The state of 'diseased' can be considered as an intermediate event. Two more states are added into the illness-death model to describe missing events caused by a loss of follow-up before the end of the study. One of them is a state of 'LTF', representing a lost-to-follow-up, and the other is an unobservable state that represents the intermediate event experienced after LTF occurred. Given covariates, we employ the Cox proportional hazards model with a normal frailty and construct a full likelihood to estimate transition intensities between states in the multi-state model. Marginalization of the full likelihood is completed using the adaptive Gaussian quadrature, and the optimal solution of the regression parameters is achieved through the iterative Newton-Raphson algorithm. Simulation studies are carried out to investigate the finite-sample performance of the proposed estimation procedure in terms of the empirical coverage probability of the true regression parameter. Our proposed method is also illustrated with the dataset adapted from Helmer et al. (2001).

• The Korean Journal of Applied Statistics
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• v.30 no.4
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• pp.539-553
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• 2017

We propose a multi-state model to analyze semi-competing risks data with interval-censored or missing intermediate events. This model is an extension of the three states of the illness-death model: healthy, disease, and dead. The 'diseased' state can be considered as the intermediate event. Two more states are added into the illness-death model to incorporate the missing events, which are caused by a loss of follow-up before the end of a study. One of them is a state of the lost-to-follow-up (LTF), and the other is an unobservable state that represents an intermediate event experienced after the occurrence of LTF. Given covariates, we employ the Lin and Ying additive hazards model with log-normal frailty and construct a conditional likelihood to estimate transition intensities between states in the multi-state model. A marginalization of the full likelihood is completed using adaptive importance sampling, and the optimal solution of the regression parameters is achieved through an iterative quasi-Newton algorithm. Simulation studies are performed to investigate the finite-sample performance of the proposed estimation method in terms of empirical coverage probability of true regression parameters. Our proposed method is also illustrated with a dataset adapted from Helmer et al. (2001).

• Journal of Intelligence and Information Systems
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• v.19 no.4
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• pp.55-79
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• 2013

In this paper, we propose a hybrid genetic algorithm (HGA) approach to effectively solve the reverse logistics network with centralized centers (RLNCC). For the proposed HGA approach, genetic algorithm (GA) is used as a main algorithm. For implementing GA, a new bit-string representation scheme using 0 and 1 values is suggested, which can easily make initial population of GA. As genetic operators, the elitist strategy in enlarged sampling space developed by Gen and Chang (1997), a new two-point crossover operator, and a new random mutation operator are used for selection, crossover and mutation, respectively. For hybrid concept of GA, an iterative hill climbing method (IHCM) developed by Michalewicz (1994) is inserted into HGA search loop. The IHCM is one of local search techniques and precisely explores the space converged by GA search. The RLNCC is composed of collection centers, remanufacturing centers, redistribution centers, and secondary markets in reverse logistics networks. Of the centers and secondary markets, only one collection center, remanufacturing center, redistribution center, and secondary market should be opened in reverse logistics networks. Some assumptions are considered for effectively implementing the RLNCC The RLNCC is represented by a mixed integer programming (MIP) model using indexes, parameters and decision variables. The objective function of the MIP model is to minimize the total cost which is consisted of transportation cost, fixed cost, and handling cost. The transportation cost is obtained by transporting the returned products between each centers and secondary markets. The fixed cost is calculated by opening or closing decision at each center and secondary markets. That is, if there are three collection centers (the opening costs of collection center 1 2, and 3 are 10.5, 12.1, 8.9, respectively), and the collection center 1 is opened and the remainders are all closed, then the fixed cost is 10.5. The handling cost means the cost of treating the products returned from customers at each center and secondary markets which are opened at each RLNCC stage. The RLNCC is solved by the proposed HGA approach. In numerical experiment, the proposed HGA and a conventional competing approach is compared with each other using various measures of performance. For the conventional competing approach, the GA approach by Yun (2013) is used. The GA approach has not any local search technique such as the IHCM proposed the HGA approach. As measures of performance, CPU time, optimal solution, and optimal setting are used. Two types of the RLNCC with different numbers of customers, collection centers, remanufacturing centers, redistribution centers and secondary markets are presented for comparing the performances of the HGA and GA approaches. The MIP models using the two types of the RLNCC are programmed by Visual Basic Version 6.0, and the computer implementing environment is the IBM compatible PC with 3.06Ghz CPU speed and 1GB RAM on Windows XP. The parameters used in the HGA and GA approaches are that the total number of generations is 10,000, population size 20, crossover rate 0.5, mutation rate 0.1, and the search range for the IHCM is 2.0. Total 20 iterations are made for eliminating the randomness of the searches of the HGA and GA approaches. With performance comparisons, network representations by opening/closing decision, and convergence processes using two types of the RLNCCs, the experimental result shows that the HGA has significantly better performance in terms of the optimal solution than the GA, though the GA is slightly quicker than the HGA in terms of the CPU time. Finally, it has been proved that the proposed HGA approach is more efficient than conventional GA approach in two types of the RLNCC since the former has a GA search process as well as a local search process for additional search scheme, while the latter has a GA search process alone. For a future study, much more large-sized RLNCCs will be tested for robustness of our approach.