• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.1039-1042
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• 1995

In real time application such as motion control, it is hard to find the application of non-causal filtering due to its need for future position data, even though it shows wide usage in off-line digital signal processing. Recently, some of motion control areas such as learning and repetitive control use non-causal filtering technique in their application. these kinds of zero-lag non-causal filter application are very usful not only to reduce the machine vibration, but also to increase control accuracy with comparatively less work. In this paper, genuine method to implement zero-lag non-causal filter in a CNC is introduced. Also the variation of this implementation for the learning operation is suggested to give the NC better control performance for a specific job. By adopting the new NC architecture call Soft-NC, all these implementions are made possible here, and especially large memory requirement which hinders their usage for many years is no longer barrier in their real world application.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.723-726
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• 2009

This paper describes a non-causal interpolative prediction method for B-picture encoding. Interpolative prediction uses correlations between neighboring pixels, including non-causal pixels, for high prediction performance, in contrast to the conventional prediction, using only the causal pixels. For the interpolative prediction, the optimal quantizing scheme has been investigated for preventing conding error power from expanding in the decoding process. In this paper, we extend the optimal quantization sceme to inter-frame prediction in video coding. Unlike H.264 scheme, our method uses non-causal frames adjacent to the prediction frame.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.6
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• pp.1025-1031
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• 2006

In this paper, a deconvolution filtering method for all-pass systems based on FIR approximation is proposed. The proposed method enables us to obtain a causal stable deconvolution filter by FIR approximating a non-causal stable deconvolution filter to a causal stable one. As we can see in this paper, the impulse response of the deconvolution filter for all-pass system is simply the mirror image of the impulse response for all-pass system itself. Due to this symmetric property between all-pass system itself and its deconvolution Inter, this method can be applied to all-pass systems without special limitation of the system's order. In order to verify the performance of the proposed method. computer simulation results for 1st-, 2nd- and 400th-order all-pass systems are included.

• Journal of the Earthquake Engineering Society of Korea
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• v.6 no.2
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• pp.39-50
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• 2002

Several pre-processing techniques for earthquake data from earthquake monitoring institutes in Korea including Korea Electric Power Research Institute are thoroughly reviewed. Among these techniques for removing an instrumental response, removing the non-causal ringing distortion by FIR filter, checking calibration status of seismic stations, and minimizing the window effect are introduced and applied to real data. It is also recommended that analysts evaluate S/N ratio in the frequency domain and consider the possibility of using the saturated earthquake data.

• Journal of The Korean Association For Science Education
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• v.14 no.2
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• pp.123-132
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• 1994

The experimental evidence evaluation of the 11th grade students(N:91) was investigated. Specially, the influence of students' ideas about optical phenomena and presented evidence types on their evidence evaluation, and the influence of students' ideas on their causal inference modes were investigated. After eliciting the students' ideas about shadow phenomena and conformity of their idea, the experimental results with a binary outcome were presented as the evidence. Then the students were asked to evaluate the evidence. Again students' ideas were elicited. Most of students had causal ideas such that the shape of object(96%) and the inclination of screen(75%) were causes of shadow shape, not the shape(70%) and color(92%) of light source. In the case of the shape of object and the color of light source, most students(70%) believed strongly their ideas. Most responses(80%) in the evidence were evidence-based, and 12% of them were theory-based. There was no significant difference of reponses types between students with causal ideas(81%) and students with non-causal ideas(78%), between covariable and non-covariable evidence. But in the case of non-causal ideas, covariable evidence was more likely to yield evidence-based reponses than non-covariable evidence. If students had preconcepts inconsistent(84%) with the evidence, they were more likely to make evidence-based responses than the students with consistent ideas (75%) with the evidence. Especially in the case perceptually biased evidence, this tendency was marked. In the case of covariable evidence, many students made inclusion inferences(40%) rather than uncertainty inferences(32%). In the case of uncertainty inferences(94%), students more likely to make evidence-based reponses than inclusion inferences(83%) and exclusion infernces(88%). In the case of inclusion inferences and exclusion infernces, students tended to make idea-based responses and distort the evidences. In conclusion, when the students evaluate the experimental evidences, their ideas influence the causal inference modes. Especially, according to the conformity of the preconcepts and logical relation of evidences, the inference modes are more strongly depended upon the preconcepts rather than evidences.

• International Journal of Highway Engineering
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• v.14 no.6
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• pp.121-129
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• 2012

PURPOSES : Traffic accidents at intersections have been increased annually so that it is required to examine the causations to reduce the accidents. However, the current existing accident models were developed mainly with non-linear regression models such as Poisson methods. These non-linear regression methods lack to reveal complicated causations for traffic accidents, though they are right choices to study randomness and non-linearity of accidents. Therefore, to reveal the complicated causations of traffic accidents, this study used structural equation methods(SEM). METHODS : SEM used in this study is a statistical technique for estimating causal relations using a combination of statistical data and qualitative causal assumptions. SEM allow exploratory modeling, meaning they are suited to theory development. The method is tested against the obtained measurement data to determine how well the model fits the data. Among the strengths of SEM is the ability to construct latent variables: variables which are not measured directly, but are estimated in the model from several measured variables. This allows the modeler to explicitly capture the unreliability of measurement in the model, which allows the structural relations between latent variables to be accurately estimated. RESULTS : The study results showed that causal factors could be grouped into 3. Factor 1 includes traffic variables, and Factor 2 contains turning traffic variables. Factor 3 consists of other road element variables such as speed limits or signal cycles. CONCLUSIONS : Non-linear regression models can be used to develop accident predictions models. However, they lack to estimate causal factors, because they select only few significant variables to raise the accuracy of the model performance. Compared to the regressions, SEM has merits to estimate causal factors affecting accidents, because it allows the structural relations between latent variables. Therefore, this study used SEM to estimate causal factors affecting accident at urban signalized intersections.

• Journal of Korean Clinical Nursing Research
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• v.14 no.3
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• pp.61-72
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• 2008

Purpose: The purpose was to identify quality of chest pain according to causal diseases and pain expression of patients with coronary artery diseases. Method: Participants were 1,964 patients with pain who visited the emergency department of A hospital from January to December 2006. Data were collected from nurses' and doctors' records as to causal disease, and quality and expression of chest pain. Results: Causal diseases were coronary artery diseases, non-specific chest pain, respiratory diseases, non-coronary artery heart diseases and digestive diseases in that order of frequency. Every disease except respiratory disease caused mostly dull and tract pain, but 63.7% of patients with coronary artery diseases complained of typical angina pain and 24.9% complained of atypical angina pain. Patients with coronary artery diseases mostly used word 'heaviness' in describing their dull pain, and 'squeezing' for tract pain. Both male and female patients who were diagnosed with coronary artery disease complained mostly frequently of dull pain and tract pain. Conclusion: The most common causal disease for patients with chest pain was coronary artery disease. Patients with other diseases also frequently complained of dull and tract pain, the same as patients with coronary artery diseases. A considerable number of patients complained various types of atypical angina pain in coronary artery diseases.

• Journal of the Institute of Convergence Signal Processing
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• v.5 no.2
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• pp.151-158
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• 2004

In this paper, an inverse filtering technique for the digital filter model is proposed. This technique enables us to obtain a stable non-causal m inverse filter by transforming (approximating) it to a causal stable inverse system. In practice, a causal FIR approximation to this inverse filter is proposed. It can be shown that the impulse response of the inverse filter for all-pass systems is simply the mirror image of the impulse response for the system. Specially, due to this symmetric property of the impulse response of all-pass systems, the proposed technique is more useful for all-pass systems than other systems. In order to illustrate the proposed inverse filtering technique, four examples are presented. Two of them are for all-pass filters. The other two examples are for IIR and FIR filters. Also, computer simulations demonstrate that the proposed technique works very well.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 2002.10b
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• pp.249-250
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• 2002

In this paper, the relationship among the 3-D surface topography parameters are studied. Several surface topography parameters that are important in tribology are calculated against various surface topography data. 3-D surface data with desired properties are generated by using the non-causal 2-D auto-regressive (AR) model. The non-causal 2-D AR model is a random 3-D surface topography model that can generate 3-D surface topography data with specified parameters.

• The Journal of the Acoustical Society of Korea
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• v.31 no.8
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• pp.487-506
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• 2012

This paper proposes a speech enhancement algorithm to improve the speech intelligibility by suppressing both reverberation and background noise. The algorithm adopts a non-causal single-channel minimum variance distortionless response (MVDR) filter to exploit an additional information that is included in the noisy-reverberant signals in subsequent frames. The noisy-reverberant signals are decomposed into the parts of the desired signal and the interference that is not correlated to the desired signal. Then, the filter equation is derived based on the MVDR criterion to minimize the residual interference without bringing speech distortion. The estimation of the correlation parameter, which plays an important role to determine the overall performance of the system, is mathematically derived based on the general statistical reverberation model. Furthermore, the practical implementation methods to estimate sub-parameters required to estimate the correlation parameter are developed. The efficiency of the proposed enhancement algorithm is verified by performance evaluation. From the results, the proposed algorithm achieves significant performance improvement in all studied conditions and shows the superiority especially for the severely noisy and strongly reverberant environment.