• Advances in concrete construction
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• v.15 no.6
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• pp.391-404
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• 2023

In this study, the modeling of the transverse connection of fully precast steel-UHPC (Ultra-High-Performance Concrete) lightweight composite bridges were conducted. The transverse connection between precast components plays a critical role in the overall performance and safety of the bridge. To achieve an accurate and reliable simulation of the interface behavior, the cohesive model in ABAQUS was employed, considering both bending-tension and compression-shear behaviors. The parameters of the cohesive model are obtained through interface bending and oblique shear tests on UHPC samples with different surface roughness. By validating the numerical simulation against actual joint tests, the effectiveness and accuracy of the proposed model in capturing the interface behavior of the fully precast steel-UHPC lightweight composite bridge were demonstrated.

• Knowledge Management Research
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• v.14 no.3
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• pp.1-13
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• 2013

This study investigates how relational activities within MNC network affect knowledge transfer and performance of subsidiary. We separated the possible relationships between headquarter and overseas subsidiaries by support level, interaction level, and conflict level, and compared the impact on knowledge transfer, and performance. To understand the knowledge sharing, development and performance, we use structural equation modeling to analyze data from subsidiaries in China.

• Journal of Digital Convergence
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• v.14 no.2
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• pp.245-258
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• 2016

This paper aims to present the way to bring about significant results through performance improvement of learning algorithm in the research applying to machine learning. Research papers showing the results from machine learning methods were collected as data for this case study. In addition, suitable machine learning methods for each field were selected and suggested in this paper. As a result, SVM for engineering, decision-making tree algorithm for medical science, and SVM for other fields showed their efficiency in terms of their frequent use cases and classification/prediction. By analyzing cases of machine learning application, general characterization of application plans is drawn. Machine learning application has three steps: (1) data collection; (2) data learning through algorithm; and (3) significance test on algorithm. Performance is improved in each step by combining algorithm. Ways of performance improvement are classified as multiple machine learning structure modeling, $+{\alpha}$ machine learning structure modeling, and so forth.

• Phonetics and Speech Sciences
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• v.11 no.2
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• pp.57-64
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• 2019

In this paper, we construct a Korean text-to-speech system using the Merlin toolkit which is an open source system for speech synthesis. In the text-to-speech system, the HMM-based statistical parametric speech synthesis method is widely used, but it is known that the quality of synthesized speech is degraded due to limitations of the acoustic modeling scheme that includes context factors. In this paper, we propose an acoustic modeling architecture that uses deep neural network technique, which shows excellent performance in various fields. Fully connected deep feedforward neural network (DNN), recurrent neural network (RNN), gated recurrent unit (GRU), long short-term memory (LSTM), bidirectional LSTM (BLSTM) are included in the architecture. Experimental results have shown that the performance is improved by including sequence modeling in the architecture, and the architecture with LSTM or BLSTM shows the best performance. It has been also found that inclusion of delta and delta-delta components in the acoustic feature parameters is advantageous for performance improvement.

• Journal of the Korean Society of Propulsion Engineers
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• v.27 no.1
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• pp.37-48
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• 2023

In this study, performance analysis modeling of two spool mixed flow type turbofan engine according to steady-state and transient is performed. The target engine is selected as F100-PW-229 from Pratt & Whitney, and main engine components including fan, high pressure compressors, combustion, high pressure turbines, low pressure turbines, mixer, convergent-divergent nozzle are modeled. The cooling effect of turbine through secondary flow path are considered in engine simulation model. We develop in-house Matlab/Simulink-based engine performance analysis program capable of analyzing internal engine state and compare it with GASTURB which is generally used as a commercial engine analysis program.

• Journal of Industrial Convergence
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• v.22 no.3
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• pp.13-25
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• 2024

This study explores research topics related to dance performances published in Korea based on big data and examines research trends that change according to the trend of the times. The results derived from topic modeling analysis are as follows. (1) Six major topics were derived: a study on marketing strategies and development plans for dance performances, (2) a study on the re-watching factors of dance performance space and performance satisfaction, (3) a study on the popularity and contribution of dance performances in the stage environment, (4) a study on the current status of dance performances and the convergence of dance group operations, (5) a study on the definition of dance performances using various social media, and (6) a study on the direction and development of technology-applied dance performance contents. Accordingly, research trends and topics related to dance, including dance performances, social changes, key keywords of researchers' change interests were extracted, and keywords were compared and analyzed to present academic changes and countermeasures. Accordingly, the need for research to apply new technologies was emphasized as it diversified and fused.

• Journal of Energy Engineering
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• v.20 no.1
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• pp.1-7
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• 2011

The performance and life-cycle costs of electric vehicle(EV) and hybrid electric vehicle(HEV) depend inherently on battery packs. Temperature uniformity in a pack is an important factor for obtaining optimum performance for an EV or HEV battery pack, because uneven temperature distribution in a pack leads to electrically unbalanced battery cells and reduced pack performance. In this work, a three-dimensional modeling was carried out to investigate the effects of operating conditions on the thermal behavior of a lithium-ion battery pack for an EV or HEV application. Thermal conductivities of various compartments of the battery were estimated based on the equivalent network of parallel/series thermal resistances of battery components. Heat generation rate in a cell was calculated using the modeling results of the potential and current density distributions of a battery cell.

• The KIPS Transactions:PartC
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• v.8C no.1
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• pp.97-104
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• 2001

In this paper, we present a new hierarchical model for performance analysis of channel allocation and packet service protocol in wireless n network. The proposed hierarchical model consists of two parts : upper and lower layer models. The upper layer model is the structure state model representing the state of the channel allocation and call service. The lower layer model, which captures the performance of the system within a given structure state, is the wireless packet retransmission protocol model. These models are developed using SRN which is an modeling tool. SRN, an extension of stochastic Petri net, provides compact modeling facilities for system analysis. To get the performance index, appropriate reward rates are assigned to its SRN. Fixed point iteration is used to determine the model parameters that are not available directly as input. That is, the call service time of the upper model can be obtained by packet delay in the lower model, and the packet generation rates of the lower model come from call generation rates of the upper model.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.37-44
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• 2001

This paper describes the modeling of work environment for the extraction of abstract operation rules for cooperative work with multiple agent. We propose the modeling method using a potential field. In the method, it is applied to a box pushing problem, which is to move a box from a start to a goal b multiple agent. The agents follow the potential value when they move and work in the work environment. The work environment is represented as the grid space. The potential field is generated by Genetic Algorithm(GA) for each agent. GA explores the positions of a potential peak value in the grid space, and then the potential value stretching in the grid space is spread by a potential diffusion function in each grid. However it is difficult to explore suitable setting using hand coding of the position of peak potential value. Thus, we use an evlolutionary computation way because it is possible to explore the large search space. So we make experiments the environment modeling using the proposed method and verify the performance of the exploration by GA. And we classify some types from acquired the environment model and extract the abstract operation rule, As results, we find out some types of the environment models and operation rules by the observation, and the performance of GA exploration is almost same as the hand coding set because these are nearly same performance on the evaluation of the consumption of agent's energy and the work step from point to the goal point.

• Phonetics and Speech Sciences
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• v.7 no.3
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• pp.139-149
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• 2015

This paper aims to analyze pronunciation variations of loanwords produced by Korean and improve the performance of pronunciation modeling of loanwords in Korean by using syllable-based segmentation and phonological knowledge. The loanword text corpus used for our experiment consists of 14.5k words extracted from the frequently used words in set-top box, music, and point-of-interest (POI) domains. At first, pronunciations of loanwords in Korean are obtained by manual transcriptions, which are used as target pronunciations. The target pronunciations are compared with the standard pronunciation using confusion matrices for analysis of pronunciation variation patterns of loanwords. Based on the confusion matrices, three salient pronunciation variations of loanwords are identified such as tensification of fricative [s] and derounding of rounded vowel [ɥi] and [$w{\varepsilon}$]. In addition, a syllable-based segmentation method considering phonological knowledge is proposed for loanword pronunciation modeling. Performance of the baseline and the proposed method is measured using phone error rate (PER)/word error rate (WER) and F-score at various context spans. Experimental results show that the proposed method outperforms the baseline. We also observe that performance degrades when training and test sets come from different domains, which implies that loanword pronunciations are influenced by data domains. It is noteworthy that pronunciation modeling for loanwords is enhanced by reflecting phonological knowledge. The loanword pronunciation modeling in Korean proposed in this paper can be used for automatic speech recognition of application interface such as navigation systems and set-top boxes and for computer-assisted pronunciation training for Korean learners of English.