• 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.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.10 no.4
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• pp.253-258
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• 2010

The causal network represents the knowledge related to the dependency relationship between all attributes. If the causal network is available, the dependency relationship can be employed to estimate the missing values for improving the estimation performance. However, the previous method had a limitation in that it did not consider the bidirectional characteristic of the causal network. The proposed method considers the bidirectional characteristic by applying prior and posterior conditions, so that it outperforms the previous method.

• Korean System Dynamics Review
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• v.1 no.2
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• pp.91-111
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• 2000

Causal maps or cognitive maps have been widely used to get insights for complex systems or decision makers. When insights come from the system behavior rather than its structure, we need simulation of causal maps and cognitive maps. In this paper, a method for directly converting causal maps and cognitive maps into stock-flow diagrams that can be simulated in computers in proposed. This method is called as NUMBER. NUMBER is an abbreviation for 'Normal Unit Modeling By Elementary Relationship'. In this paper, NUMBER is applied to a cognitive map of policy maker to show its usefulness.

• 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.

• Korean System Dynamics Review
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• v.3 no.2
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• pp.69-91
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• 2002

This paper presents an analysis of the impact of the causal looping method to the Korean middle managers' decision-making processes. The sample included the observations of decisions made by 70 groups with 5 to 7 members each. The results showed that the causal looping method was a strong device to help Korean managers followed value-focused decision processes, as opposite to alternative-focuses ones. The lessons from this study suggest a direction for the development of the education method to improve group decision-making processes.

• Journal of Preventive Medicine and Public Health
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• v.55 no.2
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• pp.116-124
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• 2022

Epidemiological studies typically examine the causal effect of exposure on a health outcome. Standardization is one of the most straightforward methods for estimating causal estimands. However, compared to inverse probability weighting, there is a lack of user-centric explanations for implementing standardization to estimate causal estimands. This paper explains the standardization method using basic R functions only and how it is linked to the R package stdReg, which can be used to implement the same procedure. We provide a step-by-step tutorial for estimating causal risk differences, causal risk ratios, and causal odds ratios based on standardization. We also discuss how to carry out subgroup analysis in detail.

• Knowledge Management Research
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• v.10 no.2
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• pp.49-63
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• 2009

In this study, sub domain of flow was investigated on literature survey, and suggested of the measuring method of web-site flow and its simulation analysis. Constructing of measuring method of flow, and using this method what-if analysis was simulated when several condition changed. Using causal map approach to extract knowledge from web-site domain experts and to derives a causal relationship of knowledge. Specially, in our study, describes method of developing and building causal map, and suggests guide line of this method on practical application. This research results show that web-site flow starts "direct searching" or "interesting of special issue(domain)", and when challenges of web-site were accorded with user's skills web-site flow grows. Further, in the web-site, information searching intention results in increase of user's duration time and experience flow to discovery new interesting issues in this process. If user's web-site of interaction is increased, awareness of environment conditions decreased, finally, user's telepresense results in increased web-site flow. This paper contained thai this method make used of measuring flow in the web-site and developing of practical strategy.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.6
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• pp.1127-1136
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• 1997

A vector timestamp is used to satisfy message ordering in a group communications. In this paper, we propose a new vector timestamp compression method which is applicable to a single process group environment where one process belongs to only one precess group. An existing compression method compares the fields of the previously sent vector timestamp with thouse of the currently updated vector timestamp, then sends only the modified fields of the vector timestamp. Unlike the previous one, a proposed compression method performs individual compression for each process using the locally maintained vector timestamp information on other processes. Also, we logicallyproved the causal ordering algorithm using the new compression method and compared the performance of the proposed method with one of the previous compression method by computer simulation. Using the proposed compression method, the message overhead required for causal ordering can be reduced.

• The Korean Journal of Applied Statistics
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• v.36 no.1
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• pp.63-83
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• 2023

Many existing studies have found significant correlations between green spaces, including urban parks, and children's happiness. Furthermore, it was implied that the area/proximity of the urban park would be effective in enhancing infancy happiness. However, inferring causal effects from observed data requires appropriate adjustment of confounding variables, and from this perspective, the causal relationship between the area of urban parks and children's happiness has not been well understood. The causal effect of urban parks on children's happiness was estimated in this study using data from the panel study on Korean children. As methods for adjusting confounding variables, regression adjustment using a regression method, weighting method, and matching method were used, and key concepts of each method were described before the analysis results. Confounders were chosen for the analysis using a directed acyclic graph. In contrast to previous research, the analysis found no significant causal relationship between the size of the city park and children's happiness.

• 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.