• Physical Therapy Korea
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• v.8 no.1
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• pp.97-106
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• 2001

Physical therapists should under stand motor control models and apply various models to evaluation and treatment of neurologically impaired patients. Thus, this paper reviews motor control models and applications in clinical settings. Assumptions and limitations of reflex models, hierarchical models, and systems models are presented. This paper also delineates goals and dissatisfaction of neurologic rehabilitation approaches for neurologically impaired patients. Muscle reeducation approach, neurotherapeutic facilitation approach, and contemporary task-oriented approach are explained.

• The KIPS Transactions:PartD
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• v.14D no.1 s.111
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• pp.89-96
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• 2007

Various classification methods have been developed to reuse components. These classification methods enable the user to access the needed components quickly and easily. Conventional classification approaches include the following problems: a labor-intensive domain analysis effort to build a classification structure, the representation of the inter-component relationships, difficult to maintain as the domain evolves, and applied to a limited domain. In order to solve these problems, this paper describes a composite cluster analysis approach for component classification. The cluster analysis approach is a combination of a hierarchical cluster analysis method, which generates a stable clustering structure automatically, and a non-hierarchical cluster analysis concept, which classifies new components automatically. The clustering information generated from the proposed approach can support the domain analysis process.

• Journal of IKEEE
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• v.23 no.2
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• pp.557-570
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• 2019

In this study, a novel hierarchical approach is investigated to extract coronary vessel from X-ray angiogram. First, we propose to combine Decimation-free Directional Filter Bank (DDFB) and Homographic Filtering (HF) in order to enhance X-ray coronary angiographic image for segmentation purposes. Because the blood vessel ensures that blood flows in only one direction on vessel branch, the DDFB filter is suitable to be used to enhance the vessels at different orientations and radius. In the combination with HF filter, our method can simultaneously normalize the brightness across the image and increases contrast. Next, a coarse-to-fine strategy for iterative segmentation based on Otsu algorithm is applied to extract the main coronary vessels in different sizes. Furthermore, we also propose a new approach to segment very small vessels. Specifically, based on information of the main extracted vessels, we introduce a new method to extract junctions on the vascular tree and level of nodes on the tree. Then, the window based segmentation is applied to locate and extract the small vessels. Experimental results on our coronary X-ray angiography dataset demonstrate that the proposed approach can outperform standard method and attain the accuracy of 71.34%.

• The Korean Journal of Applied Statistics
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• v.20 no.2
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• pp.229-244
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• 2007

Among the small area estimation methods, it has been known that hierarchical Bayesian(HB) approach is the most reasonable and effective method. However any model based approaches need good explanatory variables and finding them is the key role in the model based approach. As the lacking of explanatory variables, adopting the spatial terms in the model was introduced. Here in this paper, we evaluate the model based methods with/without spatial terms using the diagnostic methods which were introduced by Brown et al. (2001). And Economic Active Population Survey(2005) is used for data analysis.

• Smart Structures and Systems
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• v.8 no.1
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• pp.69-92
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• 2011

This paper presents an emergent pattern recognition approach based on the immune network theory and hierarchical clustering algorithms. The immune network allows its components to change and learn patterns by changing the strength of connections between individual components. The presented immune-network-based approach achieves emergent pattern recognition by dynamically generating an internal image for the input data patterns. The members (feature vectors for each data pattern) of the internal image are produced by an immune network model to form a network of antibody memory cells. To classify antibody memory cells to different data patterns, hierarchical clustering algorithms are used to create an antibody memory cell clustering. In addition, evaluation graphs and L method are used to determine the best number of clusters for the antibody memory cell clustering. The presented immune-network-based emergent pattern recognition (INEPR) algorithm can automatically generate an internal image mapping to the input data patterns without the need of specifying the number of patterns in advance. The INEPR algorithm has been tested using a benchmark civil structure. The test results show that the INEPR algorithm is able to recognize new structural damage patterns.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.37 no.5
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• pp.261-271
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• 1988

This paper presents a hierarchical algorithm of the measurement system design by system partitioning. With the increase of system size, the conventional algorithms of the optimal measurement system design confront the problems of excessive memory requirements, long computation time and cumulative computation errors. In order to overcome these problems, a hierarchical approach by system partitioning is proposed with the introduction of equivalent measurements for all the extemal measurements. This approach has the advantage of remarkable reduction in computation time and memory requirements, and guarantees sufficient calculation accuracy in its application to large power systems. The proposed algorithm has been tested for various systems, which shows its applicability to practical power systems.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.8A
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• pp.779-785
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• 2002

This paper presents a phase-based stereo matching algorithm in order to efficiently extract 3-dimensional objects from two 2D images. Conventional phase-based methods, especially using windowed Fourier phases, inherit good properties in the case of hierarchical approaches, because they basically use a multi-resolution phase map. On the contrary, their computational costs are very heavy. Therefore, a fast hierarchical approach, using multi-resolution phase-based strategy and reducing the redundancy of phase calculations, is proposed in this pare. In addition, a structural matching algorithm on the phase domain is adopted to improve the matching quality. In experimental results, it is shown that the computation loads are considerably reduced about 8 times and stable outputs are obtained.

• Asia pacific journal of information systems
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• v.30 no.2
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• pp.374-396
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• 2020

The purpose of the paper is to apply Total Interpretive Structural Modeling (TISM) used to develop a hierarchy among the key drivers and barriers to multivendor ATM Technology adoption in India from the perspectives of suppliers. TISM approach is an extension of Warfield's (IEEE Transactions: System, Man & Cybernetics 4:405-17, 1974) Interpretive Structural Modeling(ISM) approach. Based on the literature, drivers and barriers for adoption of Multivendor ATM Technology are identified. TISM is used to develop a hierarchical model which states the interpretation of relationship among these drivers and barriers. Hierarchies of all relevant drivers and barriers are developed and significant interrelationship was found out. Implications for the researchers and Industry Practitioner are highlighted. For Researchers, TISM methodology facilitates to further carry out exploratory studies by identifying the factors in technology adoption domain and focus their interactions through hierarchical structures. For Practitioners with suppliers, a list of relevant barriers and drivers to adoption of this technology in India are indications to take a decision to adopt Multivendor ATM Technology in their respective suppliers. The proposed Model developed through qualitative Modeling technique has been accomplished from the perspectives of suppliers in India in the domain of multivendor ATM Technology for the first time in ATM Banking as a contribution to the Literature.

• Communications for Statistical Applications and Methods
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• v.17 no.4
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• pp.551-560
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• 2010

This paper considers a Bayesian approach to modeling a flexible regression function under structural measurement error model. The regression function is modeled based on semiparametric regression with penalized splines. Model fitting and parameter estimation are carried out in a hierarchical Bayesian framework using Markov chain Monte Carlo methodology. Their performances are compared with those of the estimators under structural measurement error model without a semiparametric component.

• Proceedings of the IEEK Conference
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• 2003.11a
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• pp.161-164
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• 2003

This paper proposes a hierarchical approach to active shape model using wavelet transform. The proposed algorithm allows us to use both global shape characteristics and finer details for model deformation. The statistical properties of the wavelet transform of a deformable model are analyzed by principal component analysis and used as priors in the contour's deformation.