• 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 Korean Mathematical Society
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• v.34 no.2
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• pp.257-264
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• 1997

We shall introduce the concept of almost causality condition. By defining the almost causality condition we would like to examine the relationship between Woodhouse's causality principle and other known causality conditions. We show that a series of causality conditions can be characterized by using the almost causality condition.

• Journal of muscle and joint health
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• v.9 no.2
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• pp.187-202
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• 2002

This study was aim to provide rheumatoid arthritis patients the basic data of development of nursing intervention to help psychosocial adaptation of rheumatoid arthritis patients as exploring the relationship among causal perception, coping pattern, psychosocial adaptation of rheumatoid arthritis. As the results of this study the mean score of causal perception of the subjects was 3.37. The score of the internal-unstable was the highest. which was followed by extra-stable, internal factor, internal-stable, external factor and external-unstable in order among the factor of causal perception. The mean score of coping pattern was 2.64. The type of coping patterns the score of the receptive coping was the highest, which was followed by wishful coping active coping and negative coping in order among the type of coping pattern. The mean score of psychosocial adaptation was 3.28. The subconcept of psychosocial adaptation the score for personal relationship was the highest, which was followed by role function and mental state in order among the psychosocial adaptation. The analysis of the relation among causal perception, coping pattern and psychosocial adaptation showed significant negative correlation between causal perception and psychosocial adaptation(r=-0.3219, P=0.002). The analysis of the relation between the type of coping pattern and psychosocial adaptation showed significant negative correlation between psychosocial adaptation and active coping(r=-0.3210, P=0.002), negative coping(r=-0.2296, P=0.032). Only causal perception(-.36) and period of illness(-.26) effected on the psychosocial adaptation were shown to the negative direction significantly. The psychosocial adaptation was explained the 17% by these two variables. Based on this study results the factor of causal perception and the type of coping pattern of rheumatoid arthritis were shown significant relations between psychosocial adaptation. We suggests that nurses in practice apply to assessing the factor of causal perception of individuals illness and the type of coping patterns when nursing interventions in rheumatoid arthritis patients.

• 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.

• Asian Oncology Nursing
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• v.3 no.1
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• pp.66-74
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• 2003

Purpose: This study is designed to identify clusters according to the causal attribution that people make about the cancer and to determine influences of coping behavior and depression as output of causal attribution. Method: The subjects were 192 patients who had been diagnosed cancer one year ago and attended an outpatient clinic. For cancer patients to be classified homogenious groups according to causal attribution, cluster analysis of subjects' ratings on the Causal Dimension Scale was been made. Results: Cluster 1(n=71) had patients with having external, stable and uncontrollable attribution. Cluster 2(n =70) had patients with having unstable and external controllable attribution regarding cause of cancer. They were not important whether cause of cancer was self or other. Cluster 3(n=51) had patients with having internal, unstable and internal controllable attribution. Coping behaviors between cluster 1 and 3 were significant difference. However, depression was not significant difference among clusters. Conclusion: Based upon these results, it is recommended that the developing training program to be changed to the more positive attribution is necessary.

• ETRI Journal
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• v.25 no.5
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• pp.345-355
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• 2003

In this paper, we propose a method for designing a class of M-channel, causal, stable, perfect reconstruction, infinite impulse response (IIR), and parallel uniform discrete Fourier transform (DFT) filter banks. It is based on a previously proposed structure by Martinez et al. [1] for IIR digital filter design for sampling rate reduction. The proposed filter bank has a modular structure and is therefore very well suited for VLSI implementation. Moreover, the current structure is more efficient in terms of computational complexity than the most general IIR DFT filter bank, and this results in a reduced computational complexity by more than 50% in both the critically sampled and oversampled cases. In the polyphase oversampled DFT filter bank case, we get flexible stop-band attenuation, which is also taken care of in the proposed algorithm.

• Communications for Statistical Applications and Methods
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• v.23 no.1
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• pp.1-20
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• 2016

Causal inference methodologies have been developed for the past decade to estimate the unconfounded effect of an exposure under several key assumptions. These assumptions include, but are not limited to, the stable unit treatment value assumption, the strong ignorability of treatment assignment assumption, and the assumption that propensity scores be bounded away from zero and one (the positivity assumption). Of these assumptions, the first two have received much attention in the literature. Yet the positivity assumption has been recently discussed in only a few papers. Propensity scores of zero or one are indicative of deterministic exposure so that causal effects cannot be defined for these subjects. Therefore, these subjects need to be removed because no comparable comparison groups can be found for such subjects. In this paper, using currently available causal inference methods, we evaluate the effect of arbitrary cutoffs in the distribution of propensity scores and the impact of those decisions on bias and efficiency. We propose a tree-based method that performs well in terms of bias reduction when the definition of positivity is based on a single confounder. This tree-based method can be easily implemented using the statistical software program, R. R code for the studies is available online.

• The Journal of Information Systems
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• v.19 no.3
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• pp.1-12
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• 2010

Personality is comprehensive nature of the mood and attitude of people, most clearly revealed in the interaction with other people. This study is a analysis on personality type to information system security and control from financial institute employee. Based on 'The Big Five' personality model, this study develops hypothetical causal relationships of potential organization member's personality and their information system security and control. Research hypotheses are empirically tested with data collected from 901 employees. Results show that employees of high level security mind are the owner of conscientious and emotional stable personality and the employees of high level control mind are the owner of agreeable and emotional stable personality. Therefore the owner of agreeable and stable personality is higher security and control than others.

• Journal of the Korean Operations Research and Management Science Society
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• v.28 no.1
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• pp.11-23
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• 2003

This study Investigates the short and long-run dynamic relationships between the domestic and U.S. stock markets for the period of declining stock prices. It Is well known that the domestic stock market variations are largely caused by the U.S. stock market movements. Multivariate causal tty test Is utilized to examine the lead-lag relationships among four stock prices of KOSPI and KOSDAQ In the domestic part and DOWJONES and NASDAQ In the U.S. part. When the stock prices tend to decrease In the long run, It Is found that both KOSPI and KOSDAQ have closer relations with NASDAQ than DOWJONES. When both of domestic stock markets are severely fluctuate, bidirectional causal relationships appear to exist between NASDAQ and each of KOSPI and KOSDAQ. On the other hand. when the domestic stock markets are relatively stable, unidirectional causality Is found to exist between NASDAQ and each of KOSPI and KOSDAQ. which is explicitly validated by the analysis of variance decomposition.

• International Commerce and Information Review
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• v.10 no.1
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• pp.329-347
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• 2008

The purpose of this study is to examine the causal relationship between the exchange rate and economic growth, and to induce policy implications. In order to test whether time series data is stationary and the model is fitness or not, we put in operation unit root test, cointegration test. And we apply Granger causality based on an error correction model. The results indicate that uni-dierctional causality between exchange rate and economic growth is detected. Exchange rate impacts on economic growth, but economic growth don't impact on exchange rate. The analysis of impulse reaction function shows that the impulse of exchange rate impacts on Korean economic growth in negative direction. We can infer policy suggestion as follows: The fluctuation of exchange rate much affects economic growth, thus we must make a stable policy of exchange rate to continue economic growth.