• Proceedings of the Korea Society for Industrial Systems Conference
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• 1998.03a
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• pp.169-176
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• 1998

This article investigates the software acquisition problems as two dimensional : custom/pacakage and insource /outsource. The analysis adopts the cost-benefit frame work in explaining software acquisition problems and takes two leveled approach. The first level examines the cost-benefit relationship of the determinants affecting both dimensions, and these determinants are derived from theories of transaction cost, incomplete contracting, and agency. The second level focuses on the impact of general cost-benefit frivers of the software acquisition decisions. The results facilitate a broader and more detailed understanding on the software acquisition problems.

• 한국연소학회:학술대회논문집
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• 2006.04a
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• pp.89-95
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• 2006

This study has numerically modelled the combustion processes of the turbulent swirling premixed lifted flames in the low-swirl burner (LSB). In these turbulent swirling premixed flames, the four tangentially-injected air jets induce the turbulent swirling flow which plays the crucial role to stabilize the turbulent lifted flame. In the present approach, the turbulence-chemistry interaction is represented by the level-set based flamelet model. Two-dimensional and three-dimensional computations are made for the various swirl numbers and nozzle length. In terms of the centerline velocity profiles and flame liftoff heights, numerical results are compared with experimental data The three-dimensional approach yields the much better conformity with agreements with measurements without any analytic assumptions on the inlet swirl profiles, compared to the two-dimensional approach. Numerical clearly results indicate that the present level-set based flamelet approach has realistically simulated the structure and stabilization mechanism of the turbulent swirling stoichiometric and lean-premixed lifted flames in the low-swirl burner.

• Asia pacific journal of information systems
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• v.29 no.4
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• pp.771-788
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• 2019

Deep learning techniques such as Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs) show superior performance in text classification than traditional approaches such as Support Vector Machines (SVMs) and Naïve Bayesian approaches. When using CNNs for text classification tasks, word embedding or character embedding is a step to transform words or characters to fixed size vectors before feeding them into convolutional layers. In this paper, we propose a parallel word-level and character-level embedding approach in CNNs for text classification. The proposed approach can capture word-level and character-level patterns concurrently in CNNs. To show the usefulness of proposed approach, we perform experiments with two English and three Korean text datasets. The experimental results show that character-level embedding works better in Korean and word-level embedding performs well in English. Also the experimental results reveal that the proposed approach provides better performance than traditional CNNs with word-level embedding or character-level embedding in both Korean and English documents. From more detail investigation, we find that the proposed approach tends to perform better when there is relatively small amount of data comparing to the traditional embedding approaches.

• 한국전산유체공학회:학술대회논문집
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• 2011.05a
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• pp.6-9
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• 2011

In this study, the two-phase incompressible flow in two-dimensional channel considering the effect of surface tension is simulated using an improved level-set method. Quadratic element is used for solving the continuity and Navier-Stokes equations to avoid using an additional pressure equation, and Crank-Nicholson scheme and linear element are used for solving the advection equation of the level set function. Direct approach method using geometric information is implemented instead of the hyperbolic-type partial differential equation for the reinitializing the level set function. The benchmark test case considers various arrays of defomable droplets under different flow conditions in straight channel. The deformation and migration of the droplets are computed and the results are compared very well with the existing studies.

• International Journal of CAD/CAM
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• v.3 no.1_2
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• pp.67-75
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• 2003

Viewpoint-dependent feature-based modelling in computer-aided design is developed for the purposes of supporting engineering design representation and automation. The approach of this paper uses a combination of a multi-level modelling approach. This has two stages of mapping between models, and the multi-level model approach is implemented in three-level architecture. Top of this level is a feature-based description for each viewpoint, comprising a combination of form features and other features such as loads and constraints for analysis. The middle level is an executable representation of the feature model. The bottom of this multi-level modelling is a evaluation of a feature-based CAD model obtained by executable feature representations defined in the middle level. The mappings involved in the system comprise firstly, mapping between the top level feature representations associated with different viewpoints, for example for the geometric simplification and addition of boundary conditions associated with moving from a design model to an analysis model, and secondly mapping between the top level and the middle level representations in which the feature model is transformed into the executable representation. Because an executable representation is used as the intermediate layer, the low level evaluation can be active. The example will be implemented with an analysis model which is evaluated and for which results are output. This multi-level modelling approach will be investigated within the framework aimed for the design automation with a feature-based model.

• ETRI Journal
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• v.36 no.5
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• pp.714-720
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• 2014

In this paper, we propose the use of data-driven probabilistic utterance-level decision logic to improve Weighted Finite State Transducer (WFST)-based endpoint detection. In general, endpoint detection is dealt with using two cascaded decision processes. The first process is frame-level speech/non-speech classification based on statistical hypothesis testing, and the second process is a heuristic-knowledge-based utterance-level speech boundary decision. To handle these two processes within a unified framework, we propose a WFST-based approach. However, a WFST-based approach has the same limitations as conventional approaches in that the utterance-level decision is based on heuristic knowledge and the decision parameters are tuned sequentially. Therefore, to obtain decision knowledge from a speech corpus and optimize the parameters at the same time, we propose the use of data-driven probabilistic utterance-level decision logic. The proposed method reduces the average detection failure rate by about 14% for various noisy-speech corpora collected for an endpoint detection evaluation.

• 한국연소학회:학술대회논문집
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• 2003.12a
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• pp.57-61
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• 2003

In the combustion modeling of non-premixed flames, the mixture fraction conserved scalar approach is widely utilized because reactants are mixed at the molecular level before burning and atomic elements are conserved in chemical reactions. In the mixture fraction approach, combustion process is simplified to a mixing problem and the interaction between chemistry and turbulence could be modelled by many sophisticated combustion models including the flamelet model and CMC. However, most of the mixture fraction approach is restricted to one mixture system. In this study, the flamelet model based on the two-feed system is extended to the multiple fuel-feeding systems by the two mixture fraction conserved scalar approach.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.37 no.1
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• pp.1-8
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• 2014

This paper proposes an emotion classifier from EEG signals based on Bayes' theorem and a machine learning using a perceptron convergence algorithm. The emotions are represented on the valence and arousal dimensions. The fast Fourier transform spectrum analysis is used to extract features from the EEG signals. To verify the proposed method, we use an open database for emotion analysis using physiological signal (DEAP) and compare it with C-SVC which is one of the support vector machines. An emotion is defined as two-level class and three-level class in both valence and arousal dimensions. For the two-level class case, the accuracy of the valence and arousal estimation is 67% and 66%, respectively. For the three-level class case, the accuracy is 53% and 51%, respectively. Compared with the best case of the C-SVC, the proposed classifier gave 4% and 8% more accurate estimations of valence and arousal for the two-level class. In estimation of three-level class, the proposed method showed a similar performance to the best case of the C-SVC.

• Journal of the Korean Society of Combustion
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• v.12 no.3
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• pp.8-15
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• 2007

This study has numerically modelled the combustion processes of the turbulent swirling premixed lifted flames in the low-swirl burner (LSB). In these turbulent swirling premixed flames, the four tangentially-injected air jets induce the turbulent swirling flow which plays the crucial role to stabilize the turbulent lifted flame. In the present approach, the turbulence-chemistry interaction is represented by the level-set based flamelet model.. Two-dimensional and three-dimensional computations are made for the various swirl numbers and nozzle length. In terms of the centerline velocity profiles and flame liftoff heights, numerical results are compared with experimental data The three-dimensional approach yields the much better conformity with agreements with measurements without any analytic assumptions on the inlet swirl profiles, compared to the two-dimensional approach. Numerical clearly results indicate that the present level-set based flamelet approach has realistically simulated the. structure and stabilization mechanism of the turbulent swirling stoichiometric and lean-premixed lifted flames in the low-swirl burner.

• 유체기계공업학회:학술대회논문집
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• 2006.08a
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• pp.455-458
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• 2006

This study has numerically modelled the combustion processes of the turbulent swirling premixed lifted flames in the low-swirl burner (LSB). In these turbulent swirling premixed flames, the four tangentially- injected air jets induce the turbulent swirling flow which plays the crucial role to stabilize the turbulent lifted flame. In the present approach, the turbulence-chemistry interaction is represented by the level-set based flame let model. Two-dimensional and three-dimensional computations are made for the various swirl numbers and nozzle length. In terms of the centerline velocity profiles and flame liftoff heights, numerical results are compared with experimental data The three-dimensional approach yields the much better conformity with agreements with measurements without any analytic assumptions on the inlet swirl profiles, compared to the two-dimensional approach. Numerical clearly results indicate that the present level-set based flamelet approach has realistically simulated the structure and stabilization mechanism of the turbulent swirling stoichiometric and lean-premixed lifted flames in the low-swirl burner.