• 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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.12
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• pp.4275-4291
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• 2021

With the unprecedented growth of textual information on the Internet, an efficient automatic summarization system has become an urgent need. Recently, the neural network models based on the encoder-decoder with an attention mechanism have demonstrated powerful capabilities in the sentence summarization task. However, for paragraphs or longer document summarization, these models fail to mine the core information in the input text, which leads to information loss and repetitions. In this paper, we propose an abstractive document summarization method by applying guidance signals of key sentences to the encoder based on the hierarchical encoder-decoder architecture, denoted as KI-HABS. Specifically, we first train an extractor to extract key sentences in the input document by the hierarchical bidirectional GRU. Then, we encode the key sentences to the key information representation in the sentence level. Finally, we adopt key information representation guided selective encoding strategies to filter source information, which establishes a connection between the key sentences and the document. We use the CNN/Daily Mail and Gigaword datasets to evaluate our model. The experimental results demonstrate that our method generates more informative and concise summaries, achieving better performance than the competitive models.

• IE interfaces
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• v.16 no.spc
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• pp.144-148
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• 2003

A group of digital human models with various sizes which properly represents a population under consideration is needed in the design process of an ergonomic product in virtual environment. The present study proposes a two-step method which produces a representative group of human models in terms of stature and weight. The proposed method first generates a designated number of pairs of stature and weight within an accommodation range from the bivariate normal distribution of stature and weight of the target population. Then, from each pair of stature and weight, the method determines the sizes of body segments by using 'hierarchical' regression models and corresponding prediction distributions of individual values. The suggested method was applied to the 1988 US Army anthropometric survey data and implemented to a web-based system which generates a representative group of human models for the following parameters: nationality, gender, accommodation percentage, and number of human models.

• Journal of Korea Multimedia Society
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• v.11 no.4
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• pp.525-543
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• 2008

Recently, the scope of user interface is increasing the relative importance in software development dramatically. As a result, there are various relative technologies like as SWING, MFC, Web 2.0, and etc. However, most current software developments are progressed in separate development process with user interface part and business part respectively. This causes the problems, like as a difficulty in the integration process, an development period's delay, and a poor reusability for the constructed models. That is, the extendability and reusability of the created models is being decreased because UI modeling is not systematic and hierarchical, and the consistent integration technique between UI modeling and business modeling does not supported. To solve these problems, this paper proposes an unified and systematic UI modeling process based on UML, using the hierarchical metamodel according to the abstraction levels of development phase. We suggest an UI metamodel, which contains a hierarchy by layering the modeling elements in PIM and PSM based on maturity degree of the development. An hierarchical modeling process combined UI modeling and business modeling is built by applying the UI and business metamodel in terms of three modeling phases(concept/specification/concrete). The effectiveness of the modeling process is shown by applying the proposed process into an Internet Shopping Mall System. Through the exploratory results, the hierarchical UI metamodel and process can produce systematic and layered UI models. This can improve the quality and reusability of models.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2007.11a
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• pp.316-321
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• 2007

The hierarchical covering location problem emphasizes the issue of locating of hierarchical facilities in order to maximize the number of customers that can be covered. In the classical HCLP(Hierarchical Covering Location Problem), it is assumed that the customers are covered completely if they are located within a specific distance from the facility, and not covered otherwise. The generalized HCLP is introduced that the coverage of customers is measured to be any real value rather than 0 or 1, where the service level may decrease according to the distance. Mixed integer programming formulation for the generalized HCLP is suggested with a partial coverage of service. Solutions are found using OPL Studio, and are evaluated for various cases.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.29 no.3
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• pp.111-118
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• 2006

This paper presents design and development of a simulator evaluates the performance of a hierarchical cellular system. The proposed hierarchical cellular simulator, consisting of macro, micro, and pico cells, applies the wrap-around technique to reduce simulation time. The simulator is implemented as object oriented class models by using the C++ language in a PC environment. The resulting application can evaluate the interference, SIR(Signal to Interference Ratio), and capacity of a hierarchical cellular system in various configurations. Moreover, it can be used in other applications such as power control, call admission control, hand over scheme.

• The Korean Journal of Applied Statistics
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• v.28 no.2
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• pp.343-351
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• 2015

We introduce how to fit random effects models via a SRC-Stat statistical package. This package has been developed to fit double hierarchical generalized linear models where mean and dispersion parameters for the variance of random effects and residual variance (overdispersion) can be modeled as random-effect models. The estimates of fixed effects, random effects and variances are calculated by a hierarchical likelihood method. We illustrate the use of our package with practical data-sets.

• International Journal of Contents
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• v.4 no.3
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• pp.20-28
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• 2008

To obtain realistic performance measures for wireless networks, one should consider changes in performance due to failure related behavior. In performability analysis, simultaneous consideration is given to both pure performance and performance with failure measures. SRN is an extension of stochastic Petri nets and provides compact modeling facilities for system analysis. In this paper, a new methodology to model and analyze performability based on stochastic reward nets (SRN) is presented. Composite performance and availability SRN models for wireless handoff schemes are developed and then these models are decomposed hierarchically. The SRN models can yield measures of interest such as blocking and dropping probabilities. These measures are expressed in terms of the expected values of reward rate functions for SRNs. Numerical results show the accuracy of the hierarchical model. The key contribution of this paper constitutes the Petri nets modeling techniques instead of complicate numerical analysis of Markov chains and easy way of performance analysis for channel allocation under SRN reward concepts.

• Journal of the Korean Statistical Society
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• v.32 no.4
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• pp.425-448
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• 2003

Meta-analysis refers to quantitative methods for combining results from independent studies in order to draw overall conclusions. We consider hierarchical models including selection models under a skewed heavy tailed error distribution proposed originally by Chen et al. (1999) and Branco and Dey (2001). These rich classes of models combine the information of independent studies, allowing investigation of variability both between and within studies, and incorporate weight function. Here, the testing for the skewness parameter is discussed. The score test statistic for such a test can be shown to be expressed as the posterior expectations. Also, we consider the detail computational scheme under skewed normal and skewed Student-t distribution using MCMC method. Finally, we introduce one example from Johnson (1993)'s real data and apply our proposed methodology. We investigate sensitivity of our results under different skewed errors and under different prior distributions.

• Communications for Statistical Applications and Methods
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• v.10 no.1
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• pp.19-30
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• 2003

Spatiotemporal statistical models are used for analyzing space-time data in many fields, such as environmental sciences, meteorology, geology, epidemiology, forestry, hydrology, fishery, and so on. It is well known that classical spatiotemporal process modeling requires the estimation of space-time variogram or covariance functions. In practice, the estimation of such variogram or covariance functions are computationally difficult and highly sensitive to data structures. We investigate a Bayesian hierarchical model which allows the specification of a more realistic series of conditional distributions instead of computationally difficult and less realistic joint covariance functions. The spatiotemporal model investigated in this study allows both spatial component and autoregressive temporal component. These two features overcome the inability of pure time series models to adequately predict changes in trends in individual sites.