• Journal of the Korea Society of Computer and Information
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• v.18 no.8
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• pp.1-8
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• 2013

This paper proposes an effective parallel implementation of a physical modeling synthesis of guitar on the GPU environment. We used appropriate filter coefficients and adjusted the length of delay line for each open string to generate 44,100 six-polyphonic guitar sounds (E2, A2, D3, G4, B3, E4) by using physical modeling synthesis. In addition, we analyzed the physical modeling synthesis algorithm and observed that we can exploit parallelism inherent in the length of delay line. Thus, we assigned CUDA cores as many as the length of delay line and effectively implemented the physical modeling synthesis using GPU to achieve the highest performance. Experimental results indicated that synthetic guitar sounds using GPU were very similar to the original sounds when we compared their spectra. In addition, GPU achieved 68x and 3x better performance than high-performance TI DSP and CPU, respectively. Furthermore, this paper implemented and evaluated the performance of multi-GPU systems for the physical modeling algorithm.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.24 no.10
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• pp.718-723
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• 2012

The purpose of this study is to propose modeling method of Underfloor Air Distribution System with reliability and validity by comparing characteristics of modeling methods. For this, the modeling methods of UFAD were selected by investigating various modeling methods of previous researches. Then, simulations were conducted by using EnergyPlus which is dynamic analysis program of building energy. Annual energy consumption for each method was compared with a wide range of indoor thermal loads. As a result, the methodology of reducing internal gains can cause under sizing of the system. It suggests modeling methods to reflect occupied zone air-conditioning, temperature stratification and supply plenum which are the main characteristics of UFAD.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.25 no.2
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• pp.94-102
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• 2013

In this study, numerical modeling was performed to investigate influence of the apron shape on the discharge performance of the sluice for tidal power plant. The numerical modeling was carried out for comparison of the difference in the discharge coefficient when the apron width, slope, and the length of the horizontal section were different, without considering change in the shape of the sluice caisson itself. The modeling result showed that significant discrepancy in terms of the overall discharge performance appeared according to the apron geometry. In order to achieve maximum discharge performance of the sluice caisson, it is desirable to make the design by putting a space equivalent to the width of the sluice caisson on its both sides, by making the apron slope be 1:5, and by keeping length of the horizontal section to be 50 m that is corresponding to the streamwise length of the sluice caisson.

• 한국연소학회:학술대회논문집
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• 2013.06a
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• pp.21-23
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• 2013

Various solid particle materials are treated in the industrial processes including fixed-beds or moving grate beds, and modeling approaches have been widely applied to the processes to predict and evaluate their performance. For this study, the modeling approach was applied to iron ore sintering process with various improvement measures. Based on the previous modeling approach, the changes and effects of the improvement measures were discussed at the point of controlling the combustion environment in the bed.

• KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
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• v.11B no.2
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• pp.40-50
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• 2001

This paper deals with the development of the simulation models Cheju - Haenam HVDC system and its dynamic performance study and verify the control characteristics of the HVDC system. It discusses the model development requirement and criteria. It provides guedelines for developing large-scale simulation models for detailed electromagnetic studies and presents the results of the modeling project.

• International Journal of Advanced Culture Technology
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• v.12 no.1
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• pp.144-157
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• 2024

This study examines the relationship between intrinsic motivation and individuals' performance in the Republic of Korea armed forces and explores whether job stress mediates the relationship between intrinsic motivation and individuals' performance. The research questions are: (1) Does intrinsic motivation influence individual performance in military organizations? (2) Does job stress impact individual performance? and (3) Does job stress mediate the relationship between intrinsic motivation and individual performance? The study utilizes data collected from a 350 soldiers survey in the Special Forces Brigade and Special Assault Commando Regiment of the Republic of Korea's Army. We use structural equation modeling (SEM) to explore the mediation role among intrinsic motivation, job stress, and individuals' performance. Research findings suggest that intrinsic motivation negatively impacts job stress. We also find that job stress has a positive effect on firearm skills. Moreover, the study reveals that the relationship between intrinsic motivation and firearm skills is partially mediated by job stress.

• Journal of the Korean Society of Radiology
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• v.16 no.5
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• pp.595-602
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• 2022

This study tried to suggest the most efficient learning rate for accurate and efficient automatic diagnosis of medical images for chest X-ray pneumonia images using deep learning. After setting the learning rates to 0.1, 0.01, 0.001, and 0.0001 in the Inception V3 deep learning model, respectively, deep learning modeling was performed three times. And the average accuracy and loss function value of verification modeling, and the metric of test modeling were set as performance evaluation indicators, and the performance was compared and evaluated with the average value of three times of the results obtained as a result of performing deep learning modeling. As a result of performance evaluation for deep learning verification modeling performance evaluation and test modeling metric, modeling with a learning rate of 0.001 showed the highest accuracy and excellent performance. For this reason, in this paper, it is recommended to apply a learning rate of 0.001 when classifying the presence or absence of pneumonia on chest X-ray images using a deep learning model. In addition, it was judged that when deep learning modeling through the application of the learning rate presented in this paper could play an auxiliary role in the classification of the presence or absence of pneumonia on chest X-ray images. In the future, if the study of classification for diagnosis and classification of pneumonia using deep learning continues, the contents of this thesis research can be used as basic data, and furthermore, it is expected that it will be helpful in selecting an efficient learning rate in classifying medical images using artificial intelligence.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2007.11a
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• pp.265-266
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• 2007

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2008.04a
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• pp.920-927
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• 2008

This study deals with modeling of Head-Related Transfer Functions (HRTFs) using Principal Components Analysis (PCA) in the time and frequency domains. Four PCA models based on Head-Related Impulse Responses (HRIRs), complex-valued HRTFs, augmented HRTFs, and log-magnitudes of HRTFs are investigated. The objective of this study is to compare modeling performances of the PCA models in the least-squares sense and to show the theoretical relationship between the PCA models. In terms of the number of principal components needed for modeling, the PCA model based on HRIR or augmented HRTFs showed more efficient modeling performance than the PCA model based on complex-valued HRTFs. The PCA model based on HRIRs in the time domain and that based on augmented HRTFs in the frequency domain are shown to be theoretically equivalent. Modeling performance of the PCA model based on log-magnitudes of HRTFs cannot be compared with that of other PCA models because the PCA model deals with log-scaled magnitude components only, whereas the other PCA models consider both magnitude and phase components in linear scale.

• Corrosion Science and Technology
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• v.7 no.4
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• pp.197-200
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• 2008

In this paper, physical scale modeling was employed to identify the configurations of ICCP system and the electric field signatures. Computational boundary element modeling technique has been used to simulate the performance of the CP system and to predict the associated electric fields signatures. The optimization methods combined with the computer models and physical scale modeling will be presented here, which enable the optimum system design to be achieved both in terms of the location and current output of the anode but also in the location of reference electrodes for impressed current cathodic protection(ICCP) systems. The combined methodology was utilized to determine optimal placement of ICCP components (anodes and reference electrodes) and to evaluate performance of ICCP system for the 2%, 10% and 14% wetted hull coatings loss. The objective is to design the system to minimise the electric field while at the same time provide adequate protection for the ship. The results show that experimental scale modeling and computational modeling techniques can be used in concert to design an optimum ICCP system and to provide information for quickly analysis of the system and its surrounding environment.