• Journal of Internet Computing and Services
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• v.17 no.2
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• pp.11-17
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• 2016

In this paper, the optimum weight of the algorithm based on the cross information-potential with the delta functions (CIPD) is derived and its robustness against impulsive noise is studied. From the analysis of the behavior of optimum weight, it is revealed that the magnitude controlling operation for input plays the main role of keeping optimum weight of CIPD stable from the impulsive noise. The simulation results show that the steady state weight of CIPD is equivalent to that of MSE criterion. Also in the simulation environment of impulsive noise, unlike the LMS algorithm based on MSE, the steady state weight of CIPD is shown to be kept stable.

• Transactions of the Korean Society of Automotive Engineers
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• v.19 no.6
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• pp.133-139
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• 2011

Maintaining adequate sealing in engine cylinder head is a crucial factor in engine design. Failure of engine operations occurs mainly owing to the leaking by decreased sealing pressure. Reliability-robustness concept is applied to the engine cylinder head system. Deterministic way to obtain engineering solution in CAE industry may not consider the effects of noises and disturbances experienced during operation. However, analytical reliability-robustness concept may make possible to reduce the sensitivity of system with noise factors. Influences of design factors including noise factors would be predicted in analytical way. Optimized design may be obtained by shrinking variability and shifting to design target. Three-dimensional finite element analyses have been performed to apply analytical reliability-robustness concept.

• Asia pacific journal of information systems
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• v.31 no.3
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• pp.335-357
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• 2021

As reproduction of images can be done with ease, copy detection has increasingly become important. In the duplication process, image modifications are likely to occur and some alterations are deliberate and can be viewed as attacks. A wide range of copy detection techniques has been proposed. In our study, content-based copy detection, which basically applies DCT-based features for images, namely, pixel values, edges, texture information and frequency-domain component distribution, is employed. Experiments are carried out to evaluate robustness and sensitivity of DCT-based features from attacks. As different types of DCT-based features hold different pieces of information, how features and attacks are related can be shown in their robustness and sensitivity. Rather than searching for proper features, use of robustness and sensitivity is proposed here to realize how the attacked features have changed when an image attack occurs. The experiments show that, out of ten attacks, the neural networks are able to detect seven attacks namely, Gaussian noise, S&P noise, Gamma correction (high), blurring, resizing (big), compression and rotation with mostly related to their sensitive features.

• Proceedings of the KSPS conference
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• 2004.05a
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• pp.231-234
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• 2004

This paper describes an efficient method for improving the noise-robustness in speech recognition in a running car by considering wind noise. In driving car, mainly three kind of noises engine noise, tire noise and wind noise, are severely affect recognition performance. Especially wind noise is an important factor in driving car with window opened. We analyzed wind noise in various driving conditions that are 60, 80, 100 km/h with window fully opened, window half opened. We clarified that the recognition rate is significantly degenerated when the wind noise components in the frequency range above 200 Hz are large. We developed a preprocessing method to improve the noise robustness despite of wind noise. We adaptively changed the cutoff frequency of the front-end high-pass filter from 100 through 200 Hz according to the level of the wind noise components. By this method, the recognition rate is considerably improved for all kind of driving conditions

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1997.10a
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• pp.181-184
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• 1997

Practical applications of learning systems usually involve complex domains exhibiting nonlinear behavior and dilution by noise. Consequently, an intelligent system must be able to adapt to nonlinear processes as well as probabilistic phenomena. An important class of application for a knowledge based systems in prediction: forecasting the future trajectory of a process as well as the consequences of any decision made by e system. This paper examines the robustness of data mining tools under varying levels of noise while predicting nonlinear processes in the form of chaotic behavior. The evaluated models include the perceptron neural network using backpropagation (BPN), the recurrent neural network (RNN) and case based reasoning (CBR). The concepts are crystallized through a case study in predicting a Henon process in the presence of various patterns of noise.

• Journal of Information Processing Systems
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• v.13 no.2
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• pp.256-267
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• 2017

An active research area in computer vision, stereo matching is aimed at obtaining three-dimensional (3D) information from a stereo image pair captured by a stereo camera. To extract accurate 3D information, a number of studies have examined stereo matching algorithms that employ adaptive support weight. Among them, the adaptive census transform (ACT) algorithm has yielded a relatively strong matching capability. The drawbacks of the ACT, however, are that it produces low matching accuracy at the border of an object and is vulnerable to noise. To mitigate these drawbacks, this paper proposes and analyzes the features of an improved stereo matching algorithm that not only enhances matching accuracy but also is also robust to noise. The proposed algorithm, based on the ACT, adopts the truncated absolute difference and the multiple sparse windows method. The experimental results show that compared to the ACT, the proposed algorithm reduces the average error rate of depth maps on Middlebury dataset images by as much as 2% and that is has a strong robustness to noise.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.16 no.5
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• pp.113-118
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• 2017

In this paper, we propose a design procedure for determining the gate position robust to changes and inherent fluctuations in the process conditions during injection molding. To evaluate the robustness of the gate position, the signal-to-noise ratio is used, and noise conditions are implemented using orthogonal arrays, where the process variables are considered as noise factors and possible process fluctuations are set as the levels of the noise factors. To show the usefulness of the proposed robust design procedure, we apply it to a computer CPU baseplate. As a result, it is shown that a robust gate position can be determined that reduces the average warpage deflection by 2.4% and 1.7%, and the variance by 3.4% and 5.1%, compared to the two initial gate positions.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2003.11a
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• pp.729-732
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• 2003

In this paper, the transformed logo image is used as a watermark image, then the extraction rate is good when the logo image is transformed into randomly distribute Image domain. The robustness is good resist of clipping and noise.

• Structural Engineering and Mechanics
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• v.82 no.2
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• pp.245-258
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• 2022

Many Structural Health Monitoring (SHM) methods have been proposed for structural damage diagnosis and prognosis. However, SHM for pinched hysteretic structures can be problematic due to the high level of nonlinearity. The model-free hysteresis loop analysis (HLA) has displayed notable robustness and accuracy in identifying damage for full-scaled and scaled test buildings. In this paper, the performance of HLA is compared with seven other SHM methods in identifying lateral elastic stiffness for a six-story numerical building with highly nonlinear pinching behavior. Two successive earthquakes are employed to compare the accuracy and consistency of methods within and between events. Robustness is assessed across sampling rates 50-1000 Hz in noise-free condition and then assessed with 10% root mean square (RMS) noise added to responses at 250 Hz sampling rate. Results confirm HLA is the most robust method to sampling rate and noise. HLA preserves high accuracy even when the sampling rate drops to 50 Hz, where the performance of other methods deteriorates considerably. In noisy conditions, the maximum absolute estimation error is less than 4% for HLA. The overall results show HLA has high robustness and accuracy for an extremely nonlinear, but realistic case compared to a range of leading and recent model-based and model-free methods.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.13 no.6
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• pp.73-81
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• 2014

In this paper, multiple gate locations and process conditions under concern are automatically optimized by considering robustness to minimize the injection pressure required to mold an automotive dashboard. Computer simulation-based experiments using orthogonal arrays(OA) and a design-range reduction algorithm are consolidated into an iterative search scheme, which is then used as a tool for the optimization process. The robustness of a design is evaluated using an OA-based simulation of process fluctuations due to noise as well as the signal-to-noise ratio. The optimal design solution for the automotive dashboard shows that the robustness of the injection pressure is significantly improved when compared to the initial design. As a result, both the die clamping force and the pressure distribution in the part cavity are also much improved in terms of their robustness.