• Journal of Navigation and Port Research
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• v.31 no.6
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• pp.537-543
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• 2007

It's an important part to calculate the weights between criterions and to aggregate the decision inputs in a MCDM(Multi criterion decision making) This paper presents a method for aggregation cf decision inputs and application to the MCDM. We incorporate the fuzzy set theory and the basic nature of subjectivity due to ambiguity to achieve a flexible decision approach suitable for uncertain and fuzzy environments. To obtain the scoring that corresponds to the best alternative or the ranking of the alternatives, we need to use a total order for the fuzzy numbers involved in the problem. In this article, we consider a definition of such a total order, which is based on two subjective aspects: the degree of optimism/pessimism reflected with the ordered weighted averaging(OWA) oprators. A numerical example, expecially location analysis for anchorage area, is given to illustrate the approach.

• Journal of Korean Neurosurgical Society
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• v.30 no.7
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• pp.842-848
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• 2001

Objectives : The mortality rate of subarachnoid hemorrhage(SAH) has been reduced recently due to refinement of microsurgical technique and improved perioperative management. Also, many survivors of SAH show excellent neurological recoveries. However, we found that a high proportion of the survivors do not fully regain their premorbid status in cognitive and memory function. Object of this study is to evaluate which factors might influence on cognitive and memory impairment in ruptured aneurysmal SAH patients. Methods : In this prospective study, a series of 66 patients with aneurysmal subarachnoid hemorrhage(SAH) from 1996 to 1998, most of whom had a "good" or "fair" neurological outcome, were assessed with various tests of cognition and memory function. All patients underwent clipping operation by pterional approach. Right side approach was performed in 16 case and left 21 cases. K-WAIS(Korean-Wechsler Adult Intelligence Scale) was used as method of cognition and memory function test. The time interval between SAH and assessment varied between 4 months and 8 months, averaging 6.2 months. Statistical analyses were carried out for each test score to see whether aneurysm site(A-com : non A-com), route of approach, age and sex, vasospasm, Hunt-Hess grade and Fisher CT group at admission, Glasgow Outcome Scale(GOS) at discharge affect cognitive and memory function. Results : Aneurysm site was not shown to be associated with performance on any test, and the initial grade (Hunt-Hess grade, Fisher CT group) of SAH and vasospasm had only minimal predictive values. The grade at discharge( GOS) was proved to be the best predictor of impairment of cognition and memory function within 1 year after operation. Conclusion : The authors conclude that the diffuse effects of SAH are more important than focal neuropathology in relation to cognitive impairment in this group of patients.

• Proceedings of the KSME Conference
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• 2007.05b
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• pp.3353-3358
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• 2007

The present paper is devoted to investigate dynamic effect and steady-state performance of methane autothermal reformer theoretically and numerically. In order to simplify the complicated phenomena in the system, axisymmetric heterogeneous reactor model is developed. As autothermal reaction takes places on catalyst surface between bulk gas and catalyst, volume averaging method is incorporated using porous medium approach. To understand the start-up process which occurs in the reactor is highly important. Therefore, in this paper we get various goverining equations to find out transient and steady solutions and time scale for start-up introducing dimensionless variables. Start-up is a significant issue in reforming reaction for automobile system and fueling of SOFC-based auxiliary power units. This paper deals with characteristics of heat and mass transfer and predicted light-off time in the reformer as oxygen to carbon ratio ($O_2$/C) and amount of feeding gas.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.23 no.4
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• pp.347-355
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• 2013

A damage estimation method for monopile support structure of offshore wind turbine using modal properties and committee of neural networks is presented for effective structural health monitoring. An analytical model for a monopile support structure is established, and the natural frequencies, mode shapes, and mode shape slopes for the support structure are calculated considering soil condition and added mass. The input to the neural networks consists of the modal properties and the output is composed of the stiffness indices of the support structure. Multiple neural networks are constructed and each individual network is trained independently with different initial synaptic weights. Then, the estimated stiffness indices from different neural networks are averaged. Ten damage cases are estimated using the proposed method, and the identified damage locations and severities agree reasonably well with the exact values. The accuracy of the estimation can be improved by applying the committee of neural networks which is a statistical approach averaging the damage indices in the functional space.

• The Transactions of the Korean Institute of Power Electronics
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• v.19 no.5
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• pp.422-430
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• 2014

This study proposes a small-signal model and control design for a two-stage DC-DC-AC converter to investigate its dynamic characteristics in relation to battery energy storage system. When the circuit analysis of the two-stage DC-DC-AC converter is attempted simultaneously, the mathematical procedure of deriving the dynamic equation is complex and difficult. The main idea of modeling the two-stage DC-DC-AC converter states that this topology is separated into a bidirectional DC-DC converter and a single-phase inverter with an equivalent current source corresponding to that of the inverter or converter. The dynamic equations for the separated converter and inverter are then derived using the state-space averaging technique. The procedures of building the small-signal model of the two-stage DC-DC-AC converter are described in detail. Based on the derived small-signal model, the individual controllers are designed through a frequency-domain analysis. The simulation and experimental results verify the validity of the proposed modeling approach and controller design.

• International Journal of Naval Architecture and Ocean Engineering
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• v.6 no.4
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• pp.840-866
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• 2014

Visibility in underwater images is usually poor because of the attenuation of light in the water that causes low contrast and color variation. In this paper, a new approach for underwater image quality improvement is presented. The proposed method aims to improve underwater image contrast, increase image details, and reduce noise by applying a new method of using contrast stretching to produce two different images with different contrasts. The proposed method integrates the modification of the image histogram in two main color models, RGB and HSV. The histograms of the color channel in the RGB color model are modified and remapped to follow the Rayleigh distribution within certain ranges. The image is then converted to the HSV color model, and the S and V components are modified within a certain limit. Qualitative and quantitative analyses indicate that the proposed method outperforms other state-of-the-art methods in terms of contrast, details, and noise reduction. The image color also shows much improvement.

• Journal of the Institute of Convergence Signal Processing
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• v.5 no.1
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• pp.1-5
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• 2004

A new method for the estimation of pitch-frequency contour of voiced speech is presented. The method is based on the double application of Kaiser's energy operator［1］, which has the capabilities of extracting amplitude and frequency of a sinusoidal waveform. According to the modulation model, a vowel can be represented by a combination of damped sinusoids representing formants, modulated by pitch pulses. Therefore, the amplitude envelope of each of the components will give a pitch-like waveform and the pitch can be obtained by averaging the frequencies of this waveform. The first part is the same as Gopalan's approach［9］, but by substituting the LPC based spectral analysis with the second application of energy operator, the algorithm becomes very simple and can be processed on-line. Although the estimation is rather coarse, the suggested algorithm can be useful for getting a general sketch of pitch contour on-line.

• Journal of the Korean Geotechnical Society
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• v.19 no.2
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• pp.123-133
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• 2003

A practical statistical approach that can be used to model various sources of uncertainty systematically is presented in the context of reliability analysis of slope stability. New expressions for probabilistic characterization of soil properties incorporate sampling and measurement errors, as well as spatial variability and its reduced variance due to spatial averaging. The stochastic nature of seismic loading is studied by generating a large series of hazard-compatible artificial motions, and by using them in subsequent response analyses. The analyses indicate that in a seismically less active region such as the Korean Peninsular, a moderate variability in soil properties has an effect as large as the characterization of earthquake hazard on the computed risk of slope failure and excessive slope deformations.

• Advances in aircraft and spacecraft science
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• v.3 no.3
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• pp.271-298
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• 2016

In this paper, we study a problem of passive suppression of helicopter Ground Resonance (GR) using a single degree freedom Nonlinear Energy Sink (NES), GR is a dynamic instability involving the coupling of the blades motion in the rotational plane (i.e. the lag motion) and the helicopter fuselage motion. A reduced linear system reproducing GR instability is used. It is obtained using successively Coleman transformation and binormal transformation. The analysis of the steadystate responses of this model is performed when a NES is attached on the helicopter fuselage. The NES involves an essential cubic restoring force and a linear damping force. The analysis is achieved applying complexification-averaging method. The resulting slow-flow model is finally analyzed using multiple scale approach. Four steady-state responses corresponding to complete suppression, partial suppression through strongly modulated response, partial suppression through periodic response and no suppression of the GR are highlighted. An algorithm based on simple criterions is developed to predict these steady-state response regimes. Numerical simulations of the complete system confirm this analysis of the slow-flow dynamics. A parametric analysis of the influence of the NES damping coefficient and the rotor speed on the response regime is finally proposed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.4
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• pp.1975-1988
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• 2019

Short-term traffic flow prediction plays an important role in intelligent transportation systems (ITS) in areas such as transportation management, traffic control and guidance. For short-term traffic flow regression predictions, the main challenge stems from the non-stationary property of traffic flow data. In this paper, we design an ensemble cascading prediction framework based on extremely randomized trees (extra-trees) using a boosting technique called EET to predict the short-term traffic flow under non-stationary environments. Extra-trees is a tree-based ensemble method. It essentially consists of strongly randomizing both the attribute and cut-point choices while splitting a tree node. This mechanism reduces the variance of the model and is, therefore, more suitable for traffic flow regression prediction in non-stationary environments. Moreover, the extra-trees algorithm uses boosting ensemble technique averaging to improve the predictive accuracy and control overfitting. To the best of our knowledge, this is the first time that extra-trees have been used as fundamental building blocks in boosting committee machines. The proposed approach involves predicting 5 min in advance using real-time traffic flow data in the context of inherently considering temporal and spatial correlations. Experiments demonstrate that the proposed method achieves higher accuracy and lower variance and computational complexity when compared to the existing methods.