• International Journal of Fuzzy Logic and Intelligent Systems
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• v.12 no.1
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• pp.15-19
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• 2012

A Domain Dictionary generation algorithm based on pseudo feedback model is presented in this paper. This algorithm can increase the precision of domain dictionary generation algorithm. The generation of Domain Dictionary is regarded as a domain term retrieval process: Assume that top N strings in the original retrieval result set are relevant to C, append these strings into the dictionary, retrieval again. Iterate the process until a predefined number of domain terms have been generated. Experiments upon corpus show that the precision of pseudo feedback model based algorithm is much higher than existing algorithms.

• Proceedings of the Korean Society for Quality Management Conference
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• 2010.04a
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• pp.310-320
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• 2010

In this study, factors affecting the development of new products and research about the relevance of the factors based on the research model was configured. Existing research and technology commercialization process of discrimination that occur in the importance of risk management and open innovation company's competitive advantage in new product development and affect the reporter know what the effect is used as a control variable effects. Factor in the development of new products through research and innovation capacity and knowledge management activities, the introduction of open innovation and enterprise level ever due to the level of risk management controls and the need for effective research to study the model was proposed.

• Journal of Hospice and Palliative Care
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• v.14 no.2
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• pp.71-80
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• 2011

The growth of the aging population in Korea will challenge health and social services. As Korean society changes, the U.S. models of end-of-life care and geriatric care for frail older adults may have increasing relevance for the Korean healthcare system. This article reviews three U.S. models of care for frail older adults: hospice and palliative care, the Program for All-Inclusive Care for the Elderly (PACE), and the transitional care model. We describe the strengths and limitations of each model and discuss ways in which these models could be adapted for the Korean healthcare system.

• Nuclear Engineering and Technology
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• v.46 no.6
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• pp.753-772
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• 2014

The paper presents functional modelling and its application for diagnosis in nuclear power plants. Functional modelling is defined and its relevance for coping with the complexity of diagnosis in large scale systems like nuclear plants is explained. The diagnosis task is analyzed and it is demonstrated that the levels of abstraction in models for diagnosis must reflect plant knowledge about goals and functions which is represented in functional modelling. Multilevel flow modelling (MFM), which is a method for functional modelling, is introduced briefly and illustrated with a cooling system example. The use of MFM for reasoning about causes and consequences is explained in detail and demonstrated using the reasoning tool, the MFMSuite. MFM applications in nuclear power systems are described by two examples: a PWR; and an FBR reactor. The PWR example show how MFM can be used to model and reason about operating modes. The FBR example illustrates how the modelling development effort can be managed by proper strategies including decomposition and reuse.

• The Journal of Information Systems
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• v.20 no.4
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• pp.1-22
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• 2011

This study addressed trust to collective intelligence for explaining the affecting factors to the intention to use of collective intelligence by dividing the object of trust into a Web site and an information source group. We explored the factors affecting user's continuance intention toward collective intelligence in the view off trust building. We made a well-structured survey of our proposed model and gained 205 cases. We analyzed the proposed research model empirically using partial least square method. The findings are summarized as follows. First, all key factors (relevance, timeless, completeness, understandability) composing of collective intelligence quality have a positive and significant impact on confirmation. Second, confirmation has a significant impact on trust toward a Web site, as well as toward an information source group. The last is that trust toward a Web site influences on continuance intention, whereas trust toward an information source group doesn't.

• Journal of Information Processing Systems
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• v.8 no.2
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• pp.241-262
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• 2012

An understanding of quality attributes is relevant for the software organization to deliver high software reliability. An empirical assessment of metrics to predict the quality attributes is essential in order to gain insight about the quality of software in the early phases of software development and to ensure corrective actions. In this paper, we predict a model to estimate fault proneness using Object Oriented CK metrics and QMOOD metrics. We apply one statistical method and six machine learning methods to predict the models. The proposed models are validated using dataset collected from Open Source software. The results are analyzed using Area Under the Curve (AUC) obtained from Receiver Operating Characteristics (ROC) analysis. The results show that the model predicted using the random forest and bagging methods outperformed all the other models. Hence, based on these results it is reasonable to claim that quality models have a significant relevance with Object Oriented metrics and that machine learning methods have a comparable performance with statistical methods.

• Ocean Systems Engineering
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• v.5 no.1
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• pp.41-54
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• 2015

This study presents the development of predictive models for uplift capacity of suction caisson in clay using an artificial intelligence technique, extreme learning machine (ELM). Other artificial intelligence models like artificial neural network (ANN), support vector machine (SVM), relevance vector machine (RVM) models are also developed to compare the ELM model with above models and available numerical models in terms of different statistical criteria. A ranking system is presented to evaluate present models in identifying the 'best' model. Sensitivity analyses are made to identify important inputs contributing to the developed models.

• Steel and Composite Structures
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• v.6 no.5
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• pp.387-400
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• 2006

This paper discusses the composite mechanism and its effect upon the behavior of a steel reinforced concrete (SRC) member subjected to a flexural load. The relationship between member strength and deformation is established using the bond strength between the steel and reinforced concrete. An analytical model is proposed and used to incorporate the sectional strains and bond strength at the elastic and inelastic stages for moment-curvature relationship derivation. The results from the flexural load tests are used to validate the accuracy of the proposed model. Comparisons between the experimental information and the analytical results demonstrate close moment-curvature relevance, which justifies the applicability of the proposed method.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.05a
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• pp.86-88
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• 2019

In a complex geographical environment, communication quality of communication equipment is being seriously challenged. Secondary Users(SUs) must make the best possible use the idle spectrums that Primary Users(PUs) do not use and change spectrum frequently. Using the relevance vector machine(RVM) to establish a signal noise Ratio(SNR) Model for interference information and bit error rate(BER). Through the model and real-time interference information, the minimum channel SNR meeting the BER requirements of communication equipment can be predicted, and we can also calculate the minimum transmitted power. According to the simulation results, this method has better performance for selecting available channel and restraining interference.

• Earthquakes and Structures
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• v.3 no.3_4
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• pp.297-313
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• 2012

This paper is intended to show the robustness and capabilities of a coupled boundary element-finite element technique for the analysis of vibrations generated by high-speed trains under different geometrical, mechanical and operation conditions. The approach has been developed by the authors and some results have already been presented. Nevertheless, a more comprehensive study is presented in this paper to show the relevance and robustness of the method which is able to predict vibrations due to train passage at the vehicle, the track, the free-field and any structure close to the track. Local soil discontinuities, underground constructions such as underpasses, and coupling with nearby structures that break the uniformity of the geometry along the track line can be represented by the model. Non-linear behaviour of the structures can be also considered. Results concerning the excitation mechanisms, track behaviour and sub-Rayleigh and super-Rayleigh train speed are summarized in this work.