• Nuclear Engineering and Technology
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• v.54 no.11
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• pp.4359-4372
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• 2022

Turbulent mixing in buoyant flows is an essential mechanism involved in many scenarios related to nuclear safety in nuclear power plants. Comprehensive understanding and accurate predictions of turbulent buoyant flows in the reactor are of crucial importance, due to the function of mitigating the potential detrimental consequences during postulated accidents. The present study uses URANS methodology to investigate the buoyancy-influenced flows in the reactor pressure vessel under the main steam line break accident scenarios. With a particular focus on the influence of turbulent heat flux closure models, various combinations of two turbulence models and three turbulent heat flux models are utilized for the numerical simulations of three ROCOM tests which have different characteristic features in terms of the flow rate and fluid density difference between loops. The simulation results are compared with experimental measurements of the so-called mixing scalar in the downcomer and at the core inlet. The study shows that the anisotropic turbulent heat flux models are able to improve the accuracy of the predictions under conditions of strong buoyancy whilst in the weak buoyancy case, a major role is played by the selected turbulence models with essentially a negligible influence of the turbulent heat flux closure models.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.1
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• pp.24-29
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• 2022

Semantic role labeling task used in various natural language processing fields, such as information extraction and question answering systems, is the task of identifying the arugments for a given sentence and predicate. Predicate used as semantic role labeling input are extracted using lexical analysis results such as POS-tagging, but the problem is that predicate can't extract all linguistic patterns because predicate in korean language has various patterns, depending on the meaning of sentence. In this paper, we propose a korean predicate recognition method using neural network model with pre-trained embedding models and lexical features. The experiments compare the performance on the hyper parameters of models and with or without the use of embedding models and lexical features. As a result, we confirm that the performance of the proposed neural network model was 92.63%.

• Journal of Integrative Natural Science
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• v.9 no.2
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• pp.136-143
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• 2016

KiSS1-derived peptide receptor, a GPCR protein, binds with the hormone kiss peptin. They are important in the neuroendocrine regulation of reproduction and in the secretion of gonadotrophin-releasing hormone. Thus, analysing the structural features of the receptor becomes important. However, the three dimensional structure of the protein is unavailable. Hence in this study, we have performed the homology modelling of KiSS1-derived peptide receptor with 5 different templates. 30 models were constructed using two platforms - Easymodeller and ITasser. The optimal models were chosen based on the model validation. Two models were selected after validation. The developed models could provide useful for analysing the structural features of KiSS1-derived peptide receptor and their pathophysiological role in various disorders related to them.

• Journal of Korean Institute of Industrial Engineers
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• v.42 no.5
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• pp.327-336
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• 2016

Prediction of customer failure rates plays an important role for establishing appropriate management policies and improving the profitability for industries. For these reasons, many LCD (Liquid crystal display) manufacturing industries have attempted to construct prediction models for customer failure rates. However, most traditional models are based on the parametric approaches requiring the assumption that the data follow a certain probability distribution. To address the limitation posed by the distributional assumption underpinning traditional models, we propose using parameter-free data mining models for predicting customer failure rates. In addition, we use various information associated with product attributes and field return for more comprehensive analysis. The effectiveness and applicability of the proposed method were demonstrated with a real dataset from one of the leading LCD companies in South Korea.

• Journal of Information Technology Applications and Management
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• v.12 no.4
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• pp.105-121
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• 2005

Ubiquitous computing(UC) is an emerging paradigm. Its arrival as a mainstream is expected to trigger innovative UC-driven business models (UCBMs). Currently, there is no Parsimonious methodology to analyze and provide diagnostics for UCBMs. With this research, we propose a analytical architecture that enables the assessment of an UCBM in its structural strengths and weaknesses. With value logic as the cornerstone, the architecture is composed of value actors, value assets, value context, business value Propositions, customer value propositions, value creation logics, and value assumptions. Dimensional variables are initially Identified based on the review of business model literature. Then, their significance is empirically examined through 14 UCBM scenarios, and variables that are expected to Play an important role in the UCBM assessment are decided. Finally, by analyzing the scenarios in terms of the dimensional variables, we attempted to summarize general characteristics of emerging UCBMs.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.4
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• pp.626-648
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• 2011

Energy consumption of wireless access networks is in permanent increase, which necessitates development of more energy-efficient network management approaches. Such management schemes must result with adaptation of network energy consumption in accordance with daily variations in user activity. In this paper, we consider possible energy savings of wireless local area networks (WLANs) through development of a few integer linear programming (ILP) models. Effectiveness of ILP models providing energy-efficient management of network resources have been tested on several WLAN instances of different sizes. To cope with the problem of high computational time characteristic for some ILP models, we further develop several heuristic algorithms that are based on greedy methods and local search. Although heuristics obtains somewhat higher results of energy consumption in comparison with the ones of corresponding ILP models, heuristic algorithms ensures minimization of network energy consumption in an amount of time that is acceptable for practical implementations. This confirms that network management algorithms will play a significant role in practical realization of future energy-efficient network management systems.

• Journal of Korean Society for Atmospheric Environment
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• v.16 no.E2
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• pp.97-103
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• 2000

A Thermal Internal Boundary Layer(TIBL) develops over the landside from the coast due to the surface temperature difference between the land the sea when sea breeze froms. The TIBL plays an important role in determining the pollutant concentrations where the plume emitted from a tall stack near the coast fumigates to the ground. The fumigation results in the high ground the TIBL height from the available meterological data is very important. The TIBL models avaliable in the literature were analyzed to identify the suitable model to apply in the fumigation. The TIBL heights predicted by the existing models were compared with the measurements in the water tank experiment. The results show that the TIBL models by Raynor is appropriate to predict the height of TIBL.

• International Commerce and Information Review
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• v.4 no.2
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• pp.97-119
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• 2002

This research purposes on comparing some e-trailing models in character and presenting the obstacles of e-trailing activation and the solutions, e-trailing models this research has studied are 1) Bolero, 2) TradeCard, 3) BeXcom, 4) Identrus, and 5) TEDI etc. Comparing characteristic points of the e-trading models are as follows ; 1) Access ways as a global e-trading model, 2) Structural characteristic, 3) Functional characteristic, 4) Role as a global e-trading model, 5) Legal issues, 6) Application issues in practice, 7) Security issues for Technology.

• Journal of ILASS-Korea
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• v.9 no.3
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• pp.42-49
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• 2004

The present article investigates the influence of droplet drag models on predictions of diesel spray behaviors under ultra-high injection pressure conditions. To consider drop deformation and shock disturbance, this study introduces a new hybrid model in predicting drag coefficient from the literature findings. Numerical simulations are first conducted on transient behaviors of single droplet to compare the hybrid model with earlier conventional model. Moreover, using two different models, extensive numerical calculations are made for diesel sprays under ultra-high pressure sprays. It is found that the droplet drag models play an important role in determining the transient behaviors of sprays such as spray tip velocity and penetration lengths. Numerical results indicate that this new hybrid model yields the much better conformity with measurements especially under the ultra-high injection pressure conditions.

• Korean Institute of Interior Design Journal
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• no.41
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• pp.266-274
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• 2003

Synectics is one of several techniques used to enhance brainstorming by taking a more active role and introducing metaphor and structure into the process. It is unclear at what level of specificity this should be formulated as a pattern. This thesis reviews recent computational as well as experimental work on analogical reasoning based on synectics. New results regarding information processing of analogical reasoning stages, major computational models and recent attempts to compare these models are reviewed. Computational models are also discussed in the computational as well as cognitive psychology perspectives. Future directions in analogical reasoning research are proposed. The following import is the need to accommodate the typology and normal assessment in the concrete circumstances where actual reasoning and problem solving take place. In order to get to this end, we used computational models by Thagard who take the stand of ‘Computational Philosophy of Science’, which assumes ‘Weak AI’ to explicate what constitute the very pecularity of Analogical Reasoning.