• Journal of the Korean Operations Research and Management Science Society
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• v.22 no.3
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• pp.163-173
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• 1997

Although numerous studies demonstrate that one technique outperforms the others for a given data set, it is hard to tell a priori which of these techniques will be the most effective to solve a specific problem. It has been suggested that the better approach to classification problem might be to integrate several different forecasting techniques by combining their results. The issues of interest are how to integrate different modeling techniques to increase the predictive performance. This paper proposes the post-model integration method, which tries to find the best combination of the results provided by individual techniques. To get the optimal or near optimal combination of different prediction techniques, Genetic Algorithms (GAs) are applied, which are particularly suitable for multi-parameter optimization problems with an object function subject to numerous hard and soft constraints. This study applies three individual classification techniques (Discriminant analysis, Logit model and Neural Networks) as base models for the corporate failure prediction. The results of composite predictions are compared with the individual models. Preliminary results suggests that the use of integrated methods improve the performance of business classification.

• Journal of Communications and Networks
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• v.10 no.2
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• pp.148-155
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• 2008

In wireless data communication systems, retransmission of an erroneous packet is inevitable due to the harsh communication environment. In this paper, an efficient retransmission scheme using cooperation from neighboring nodes is investigated. In the cooperative retransmission scheme, an erroneous packet is transmitted to the destination by cooperative nodes which have favorable channels. This cooperative retransmission scheme requires no a priori information of neighboring nodes and has no limitation on the number of cooperating nodes. Distributed beamforming is used to accommodate multiple cooperating nodes. Phase and frequency offsets of cooperating signals are extracted from the NACK message and used to co-phase retransmitted data packets. The outage probability of the cooperative retransmission scheme is analyzed for the case of perfect synchronization and when the offsets are estimated. To reduce the impact of the residual phase and frequency offsets in cooperating signals, a low-rate feedback scheme is also investigated. It is shown that improved outage probability and reduced packet error rate (PER) performance can be achieved even for long data packets. The proposed cooperative retransmission scheme is found to outperform simple retransmission by the source as well as decode-and-forward cooperation.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.23 no.3
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• pp.282-290
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• 2013

A new method is presented that uses guided wave techniques for sludge and blockages detection in long-range pipelines. Existing techniques have the limitations that the sludge position needs to be known a priori and the area to be inspected needs to be accessible. Two guided wave techniques have been developed which allow the sludge or blockages to be detected remotely without the need to access the specific location where the pipe is blocked, nor to open the pipe. The first technique measures the reflection of guided waves by sludge which can be used to accurately locate the blocked region; the second technique detects sludge by revealing the changes to the transmitted guided waves propagating in the blocked region or after it. The two techniques complement each other and their combination leads to a reliable sludge or blockage detection. Various types of realistic sludge have been considered in the study and the practical capabilities of the two techniques have been demonstrated.

• Korea-Australia Rheology Journal
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• v.13 no.1
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• pp.37-45
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• 2001

Numerical simulation of coextrusion process of viscoelastic fluids within a die has been carried out. In the coextrusion process velocity profile at the outflow boundary is not known a priori, which makes it difficult to impose the proper boundary condition at the outflow boundary. This difficulty has been avoided by using the open boundary condition (OBC) method. In this study, elastic viscous stress splitting (EVSS) formulation with streamline upwind (SU) method has been used in the finite element method. In order to test the validity of the OBC method, comparison between the results of fully developed condition at the outlet and those of OBC has been made for a Newtonian fluid. In the case of upper convected Maxwell (UCM) fluid, the effect of outflow boundary condition on the interface position has been investigated by using two meshes having different downstream lengths. In both cases, the results with the OBC method showed reasonable interface shape. In particular, for the UCM fluid the interface shape calculated with OBC was independent of the downstream length, while the results with the zero traction condition showed oscillation of interface position close to the outlet. Viscosity difference was found to be more important than elasticity difference in determining the final interface position. However, the overshoot of interface position near the con-fluent point increased with elasticity.

• The Journal of Engineering Research
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• v.2 no.1
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• pp.49-56
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• 1997

In emission computed tomography, statistical reconstruction methods in the context of a Bayesian framework have been a topic of interest over the last decade. This was mainly due to the fact that Bayesian approaches can incorporate a priori information into the reconstruction algorithm. Although these approaches can exhibit good performance, their applications to the clinic is hindered mainly by their high computational cost. On the other hand, the speed and simplicity of the filtered backprojection (FBP) algorithm have led to its widespread use in most clinical applications. In this work, we use spline models, which have been quite useful in Bayesian reconstruction, as regularizers for high-frequency apodization in FBP algorithm and show that the effects of using spline models as priors in Bayesian reconstruction can also be achieved in FBP reconstruction.

• Journal of Korea Society of Digital Industry and Information Management
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• v.6 no.2
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• pp.55-69
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• 2010

This article proposed the authentication protocol for peer-to-peer resource sharing community. The proposed protocol does not require a priori information for generating and exchanging authentication key. Also this protocol can provide the delicate access control by allowing the user(authenticator) to assign the trust level to the authentication supplicant, which can be used to decide if the resource providing node will accept the resource sharing request from a resource requesting node. Trust Relationship Chaining provides the environment where trust levels (included in the trust table) of nodes in the resource sharing community are propagated among nodes when trust tables are exchanged between two nodes engaged in mutual authentication process and authentication refresh so that any two nodes which are not directly mutual-authenticated can assign the trust level each other for the access control for resource sharing. In the proposed protocol a node can implements the authentication refresh continuously to verify the effectiveness of authentication after mutual authentication so that the authentication of new node or authentication revocation(effectiveness cancellation) of the departed node can be propagated to the all the nodes in RSC and eventually safe resource sharing community is configured.

• Journal of Biomedical Engineering Research
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• v.22 no.4
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• pp.311-319
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• 2001

Statistical reconstruction methods in the context of a Bayesian framework have played an important role in emission tomography since they allow to incorporate a priori information into the reconstruction algorithm. Given the ill-posed nature of tomographic inversion and the poor quality of projection data, the Bayesian approach uses regularizers to stabilize solutions by incorporating suitable prior models. In this work we show that, while the quantitative performance of the standard filtered backprojection (FBP) algorithm is not as good as that of Bayesian methods, the application of spline-regularized smoothing to the sinogram space can make the FBP algorithm improve its performance by inheriting the advantages of using the spline priors in Bayesian methods. We first show how to implement the spline-regularized smoothing filter by deriving mathematical relationship between the regularization and the lowpass filtering. We then compare quantitative performance of our new FBP algorithms using the quantitation of bias/variance and the total squared error (TSE) measured over noise trials. Our numerical results show that the second-order spline filter applied to FBP yields the best results in terms of TSE among the three different spline orders considered in our experiments.

• Journal of Astronomy and Space Sciences
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• v.26 no.1
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• pp.59-74
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• 2009

Relative navigation system is presented using GPS measurements from a single-channel global positioning system (GPS) simulator. The objective of this study is to provide the real-time inter-satellite relative positions as well as absolute positions for two formation flying satellites in low earth orbit. To improve the navigation performance, the absolute states are estimated using ion-free GRAPHIC (group and phase ionospheric correction) pseudo-ranges and the relative states are determined using double differential carrier-phase data and singled-differential C/A code data based on the extended Kalman filter and the unscented Kalman filter. Furthermore, pseudo-relative dynamic model and modified relative measurement model are developed. This modified EKF method prevents non-linearity of the measurement model from degrading precision by applying linearization about absolute navigation solutions not about the priori estimates. The LAMBDA method also has been used to improve the relative navigation performance by fixing ambiguities to integers for precise relative navigation. The software-based simulation has been performed and the steady state accuracies of 1 m and 6 mm ($1{\sigma}$ of 3-dimensional difference errors) are achieved for the absolute and relative navigation using EKF for a short baseline leader/follower formation. In addition, the navigation performances are compared for the EKF and the UKF for 10 hours simulation, and relative position errors are mm-level for the two filters showing the similar trends.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.33 no.8
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• pp.580-588
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• 2009

This paper summarizes the experimentally-measured performance of small-scale, vertical-axis wind turbine for the purpose of improving the aerodynamic efficiency and its controllability. The turbine is designed to have a Savonius-Type rotor with an inlet guide-vane and an side guide-vane so that it achieves a higher efficiency than any lift- or drag-based turbines. The main design factors for this high-efficient, vertical wind turbine are the number of blades (Z), and the aspect ratio of Height/Diameter (H/D) among many. The basic model has the diameter of 580mm, the height of 464mm, and the blade number of 10. The maximum power coefficient of 0.50 was experimentally measured for the above-mentioned specifications. The inlet-guide vane ensures the maximum efficiency when the angle of attack to the rotor blade lies between $15^{\circ}$ and $20^{\circ}$. This experimental results for the vertical-axis wind turbine can be applied to the preliminary design of turbine output curve based on the wind characteristics at the proposed site by controlling its aerodynamic performance given as a priori.

• Journal of Intelligence and Information Systems
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• v.4 no.2
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• pp.23-34
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• 1998

Travel time forecasting, especially public bus travel time forecasting in urban areas, is a difficult and complex problem which requires a prohibitively large computation time and years of experience. As the network of target area grows with addition of streets and lanes, computational burden of the forecasting systems exponentially increases. Even though the travel time between two neighboring intersections is known a priori, it is still difficult, if not impossible, to compute the travel time between every two intersections. For the reason, previous approaches frequently have oversimplified the transportation network to show feasibilities of the problem solving algorithms. In this paper, forecasting of the travel time between every two intersections is attempted based on travel time data between two neighboring intersections. The time stamps data of public buses which recorded arrival time at predetermined bus stops was extensively collected and forecast. At first, the time stamp data was categorized to eliminate white noise, uncontrollable in forecasting, based on wavelet conversion. Then, the radial basis neural networks was applied to remaining data, which showed relatively accurate results. The success of the attempt was confirmed by the drastically reduced relative error when the nodes between the target intersections increases. In general, as the number of the nodes between target intersections increases, the relative error shows the tendency of sharp increase. The experimental results of the novel approaches, based on wavelet conversion and neural network teaming mechanism, showed the forecasting methodology is very promising.