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

• Journal of the Korea Institute of Building Construction
• /
• v.17 no.6
• /
• pp.535-544
• /
• 2017

This paper analyzes the relations between design errors, prevented by building information modeling (BIM)-based design validation, and their impacts in order to identify critical consideration factors for implementing BIM-based design validation in architecture, engineering, and construction (AEC) projects. More than 800 design errors detected by BIM-based design validation in two BIM-based projects in South Korea are categorized according to their causes (illogical error, discrepancy, and missing item) and work types (structure, architecture, and mechanical, electrical, and plumbing (MEP)). The probabilistic relations among the independent variables, including the causes and work types of design errors, and the dependent variables, including the project delays, cost overruns, low quality, and rework generation that can be caused by these errors, are analyzed using logistic regression. The characteristics of each design error are analyzed by means of face-to-face interviews with practitioners. According to the results, the impacts of design error causes in predicting the probability values of project delays, cost overruns, low quality, and rework generation were statistically meaningful.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.23 no.5
• /
• pp.1310-1318
• /
• 1998

Sigma-delta converter is frequently used for conyerting low-frequency anglog to digital signal. The converter consists of a modulator and a digital filer, but our work is concentrated on the modulator. In this works, to design second-order sigma-dalta modulator with 14bit resolution, we define maximumerror limits of each components (operational smplifier, integrator, internal ADC, and DAC) of modulator. It is first performed modeling of an ideal second-order sigma-delta modulator. This is then modified by adding the non-ideal factors such as limit of op-amp output swing, the finit DC gain of op-amp slew rate, the integrator gian error by the capacitor mismatch, the ADC error by the cmparator offset and the mismatch of resistor string, and the non-linear of DAC. From this modeling, as it is determined the specification of each devices requeired in design and the fabrication error limits, we can see the final performance of modulator.

• Journal of The Korean Society of Agricultural Engineers
• /
• v.47 no.4
• /
• pp.65-74
• /
• 2005

AnnAGNPS model was applied to a catchment mainly occupied with bushland for modeling non-point source pollution. Since the single event model cannot handle events longer than 24 hours duration, the event-based calibration was carried out using the continuous mode. As event flows affect sediment and nutrient generation and transport, the calibration of the model was performed in three steps: Hydrologic, Sediment and Nutrient calibrations. The results from hydrologic calibration for the catchment indicate a good prediction of the model with average ARE(Absolute Relative Error) of $24.6\%$ fur the runoff volume and $12\%$ for the peak flow. For the sediment calibration, the average ARE was $198.8\%$ indicating acceptable model performance for the sediment prediction. The predicted TN(Total Nitrogen) and TP(Total Phosphorus) were also found to be acceptable as the average ARE for TN and TP were $175.5\%\;and\;126.5\%$, respectively. The AnnAGNPS model was therefore approved to be appropriate to model non-point source pollution in bushland catchments. In general, the model was likely to result in underestimation for the larger events and overestimation fur the smaller events for the water quality predictions. It was also observed that the large errors in the hydrologic prediction also produced high errors in sediment and nutrient prediction. This was probably due to error propagation in which the error in the hydrologic prediction influenced the generation of error in the water quality prediction. Accurate hydrologic calibration should be hence obtained for a reliable water quality prediction.

• Journal of Navigation and Port Research
• /
• v.28 no.3
• /
• pp.161-167
• /
• 2004

Maritime safety and marine environmental protection are the most important topic in marine society. But, so many marine accidents have been occurred with the development of marine transportation industry. On the other side, ship is being operated under a highly dynamic environment and many factors are related with ship's collision Nowadays, the increasing tendency to the human errors of ship's collision is remarkable, and the investigation of the human errors has been heavily concentrated. This study analysed on the human errors of ship's collision related to the negligence of lookout and classified basic error type using GEMS(Generic Error Modeling System) dynamic model.

• Journal of the Korean Institute of Telematics and Electronics S
• /
• v.35S no.10
• /
• pp.64-76
• /
• 1998

In this paper, we propose the dynamic modeling, path planning and tracking algorithms of 4-wheeled 2-d.o.f.(degree of freedom) mobile robot(WMR). The gaussian functions are applied to design the smooth path of WMR. To calculate the WMR position in real time, we use three components of inertial measurement units(IMU). These units have initial error because of the rotation rate of earth, gravity acceleration and so on. Therefore we derive the initial error model of IMU, and compare the fitness diagnosis about probability characteristics of real data adn estimated data. The performance of IMU with error model and Kalman filter is compared to that without filter and error model. The simulation results show that the proposed dynamic model, path planning and tracking algorithms are more useful than the conventional control algorithm.

• JSTS:Journal of Semiconductor Technology and Science
• /
• v.11 no.4
• /
• pp.262-271
• /
• 2011

In this work, we present a unified analytical surface potential model, valid for both PD and FD SOI MOSFETs. Our model is based on a simplified one dimensional and purely analytical approach, and builds upon an existing model, proposed by Yu et al. [4], which is one of the most recent compact analytical surface potential models for SOI MOSFETs available in the literature, to improve its accuracy and remove its inconsistencies, thereby adding to its robustness. The model given by Yu et al. [4] fails entirely in modeling the variation of the front surface potential with respect to the changes in the substrate voltage, which has been corrected in our modified model. Also, [4] produces self-inconsistent results due to misinterpretation of the operating mode of an SOI device. The source of this error has been traced in our work and a criterion has been postulated so as to avoid any such error in future. Additionally, a completely new expression relating the front and back surface potentials of an FD SOI film has been proposed in our model, which unlike other models in the literature, takes into account for the first time in analytical one dimensional modeling of SOI MOSFETs, the contribution of the increasing inversion charge concentration in the silicon film, with increasing gate voltage, in the strong inversion region. With this refinement, the maximum percent error of our model in the prediction of the back surface potential of the SOI film amounts to only 3.8% as compared to an error of about 10% produced by the model of Yu et al. [4], both with respect to MEDICI simulation results.

• Journal of KIISE:Computer Systems and Theory
• /
• v.31 no.5_6
• /
• pp.288-296
• /
• 2004

This paper proposes a new mesh simplification algorithm using differential error metric. Many simplification algorithms make use of a distance error metric, but it is hard to measure an accurate geometric error for the high-curvature region even though it has a small distance error measured in distance error metric. This paper proposes a new differential error metric that results in unifying a distance metric and its first and second order differentials, which become tangent vector and curvature metric. Since discrete surfaces may be considered as piecewise linear approximation of unknown smooth surfaces, theses differentials can be estimated and we can construct new concept of differential error metric for discrete surfaces with them. For our simplification algorithm based on iterative edge collapses, this differential error metric can assign the new vertex position maintaining the geometry of an original appearance. In this paper, we clearly show that our simplified results have better quality and smaller geometry error than others.

• Special Issue of the Society of Naval Architects of Korea
• /
• 2013.12a
• /
• pp.35-41
• /
• 2013

Nowadays, automated modeling system for steel margin based on interactive user interface has been developed and applied to the production design stage. The system could increase design efficiency and minimize human error owing to recent CAD technique. However, there has been no approach to the pre-nesting design stage at all in early modeling process especially where ship model should be handled at more than two design stages using AVEVA Marine. A designer of the design stage needs artificial intelligence system beyond modeling automation when 3D model must be prepared in early modeling process using AVEVA Marine because they have focused on 2D nesting traditionally. In addition, they have a hard time figuring out the model prepared in previous design stage and modifying the model for steel purchase size in early modeling process. In this paper, artificial intelligence modeling system for automated application of steel margin in early modeling process using AVEVA Marine is developed in order to apply to the pre-nesting design stage that can detect effective segments before a calculation to find if a segment locates near block butt boundaries by filtering noise segments among lines, curves and surface intersections based on IT big data analysis.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.12 no.6
• /
• pp.577-582
• /
• 2002

Neural network can be trained to approximate an arbitrary nonlinear function of multivariate data like the mini-mill crown values in Automatic Shape Control. The trained weights of neural network can evaluate or generalize the process data outside the training vectors. Sometimes, the blind modeling of the process data is necessary to compare with the scattered analytical model of mini-mill process in isolated electro-mechanical forms. To come up with a viable model, we propose the blind neural-based range-division domain-clustering piecewise-linear modeling scheme. The basic ideas are: 1) dividing the range of target data, 2) clustering the corresponding input space vectors, 3)training the neural network with clustered prototypes to smooth out the convergence and 4) solving the resulting matrix equations with a pseudo-inverse to alleviate the ill-conditioning problem. The simulation results support the effectiveness of the proposed scheme and it opens a new way to the data analysis technique. By the comparison with the statistical regression, it is evident that the proposed scheme obtains better modeling error uniformity and reduces the magnitudes of errors considerably. Approximatly 10-fold better performance results.