• International journal of advanced smart convergence
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• v.5 no.4
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• pp.15-20
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• 2016

When a virtual sound source for 3D auditory system is reproduced by a linear loudspeaker array, listeners can perceive not only the direction of the source, but also its distance. Control over perceived distance has often been implemented via the adjustment of various acoustic parameters, such as loudness, spectrum change, and the direct-to-reverberant energy ratio; however, there is a neglected yet powerful cue to the distance of a nearby virtual sound source that can be manipulated for sources that are positioned away from the listener's median plane. This paper address the problem of generating binaural signals for moving sources in closed or in open environments. The proposed perceptual enhancement algorithm composed of three main parts is developed: propagation, reverberation and the effect of the head, torso and pinna. For propagation the effect of attenuation due to distance and molecular air-absorption is considered. Related to the interaction of sounds with the environment, especially in closed environments is reverberation. The effects of the head, torso and pinna on signals that arrive at the listener are also objectives of the consideration. The set of HRTF that have been used to simulate the virtual sound source environment for 3D auditory system. Special attention has been given to the modelling and interpolation of HRTFs for the generation of new transfer functions and definition of trajectories, definition of closed environment, etc. also be considered for their inclusion in the program to achieve realistic binaural renderings. The evaluation is implemented in MATLAB.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.24 no.5
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• pp.94-105
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• 2010

To detect faults in an inverter-fed permanent magnet synchronous motor (PMSM) drive under the circumstance having faults in a stator winding and inverter switch, an on-line basis fault detecting scheme during operation is presented. The proposed scheme is achieved by monitoring the second-order harmonic component in q-axis current and the fault is detected by comparing these components with those in normal conditions. The linear interpolation method is employed to determine the harmonic data in normal operating conditions. As soon as the fault is detected, the operating mode is changed to identify a fault type using the phase current waveform. To verify the effectiveness of the proposed fault detecting scheme, a test motor to allow inter-turn short in the stator winding has been built. The entire control algorithm is implemented using DSP TMS320F28335. Without requiring an additional hardware, the fault can be effectively detected by the proposed scheme during operation so long as the steady-state condition is satisfied.

• The Transactions of the Korean Institute of Power Electronics
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• v.15 no.3
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• pp.167-178
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• 2010

To diagnose a stator winding fault caused by a short-circuited turn in a permanent magnet synchronous motor (PMSM), an on-line based fault detecting scheme during motor operation is presented. The proposed scheme is based on monitoring the second-order harmonic components in q-axis current obtained through the harmonic analysis and a winding fault is detected by comparing these components with those in normal conditions. The linear interpolation method is employed to determine harmonic data in arbitrary normal operating conditions. To verify the effectiveness of the proposed fault detecting scheme, a test motor to allow inter-turn short in the stator winding has been built. The entire control system including harmonic analysis algorithm and fault detecting algorithm is implemented using DSP TMS320F28335. The proposed scheme does not require any additional hardware and can effectively detect a fault during motor operation so long as the steady-state condition is satisfied.

• International Journal of Naval Architecture and Ocean Engineering
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• v.8 no.4
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• pp.301-311
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• 2016

This paper describes the whole procedures to determine ice-induced global loads on the ship using measured full-scale data in accordance with the method proposed by the Canadian Hydraulics Centre of the National Research Council of Canada. Ship motions of 6 degrees of freedom (dof) are found by processing the commercial sensor signals named Motion Pak II under the assumption of rigid body motion. Linear accelerations as well as angular rates were measured by Motion Pak II data. To eliminate the noise of the measured data and the staircase signals due to the resolution of the sensor, a band pass filter that passes frequencies between 0.001 and 0.6 Hz and cubic spline interpolation resampling had been applied. 6 dof motions were computed by the integrating and/or differentiating the filtered signals. Added mass and damping force of the ship had been computed by the 3-dimensional panel method under the assumption of zero frequency. Once the coefficients of hydrodynamic and hydrostatic data as well as all the 6 dof motion data had been obtained, global ice loads can be computed by solving the fully coupled 6 dof equations of motion. Full-scale data were acquired while the ARAON rammed old ice floes in the high Arctic. Estimated ice impact forces for two representative events showed 7e15 MN when ship operated in heavy ice conditions.

• Journal of the Korea Computer Graphics Society
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• v.3 no.2
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• pp.27-34
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• 1997

3-D image modeling is in high demand for automated visual inspection and non-destructive testing. It also can be useful in biomedical research, medical therapy, surgery planning, and simulation of critical surgery (i.e. cranio-facial). Image processing and image analysis are used to enhance and classify medical volumetric data. Analyzing medical volumetric data is very difficult In this paper, we propose a new image modeling method based on tetrahedrization to improve the visualization of three-dimensional medical volumetric data. In this method, the trivariate piecewise linear interpolation is applied through the constructed tetrahedral domain. Also, visualization methods including iso-surface, color contouring, and slicing are discussed. This method can be useful to the correct and speedy analysis of medical volumetric data, because it doesn't have the ambiguity problem of Marching Cubes algorithm and achieves the data reduction. We expect to compensate the degradation of an accuracy by using an adaptive sub-division of tetrahedrization based on least squares fitting.

• The KIPS Transactions:PartB
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• v.12B no.7 s.103
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• pp.795-802
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• 2005

In this paper, we present a facial expression recognition-synthesis system that recognizes 7 basic emotion information automatically and renders face with non-photorelistic style in PDA For the recognition of the facial expressions, first we need to detect the face area within the image acquired from the camera. Then, a normalization procedure is applied to it for geometrical and illumination corrections. To classify a facial expression, we have found that when Gabor wavelets is combined with enhanced Fisher model the best result comes out. In our case, the out put is the 7 emotional weighting. Such weighting information transmitted to the PDA via a mobile network, is used for non-photorealistic facial expression animation. To render a 3-D avatar which has unique facial character, we adopted the cartoon-like shading method. We found that facial expression animation using emotional curves is more effective in expressing the timing of an expression comparing to the linear interpolation method.

• Journal of Korea Multimedia Society
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• v.12 no.8
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• pp.1089-1098
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• 2009

Recently, many researches of making more comfortable input device based on gaze detection technology have been performed in human computer interface. Previous researches were performed on the computer environment with a large sized monitor. With recent increase of using mobile device, the necessities of interfacing by gaze detection on mobile environment were also increased. In this paper, we research about the gaze detection method by using UMPC (Ultra-Mobile PC) and an embedded camera of UMPC based on face and facial feature detection by AAM (Active Appearance Model). This paper has following three originalities. First, different from previous research, we propose a method for tracking user's gaze position in mobile device which has a small sized screen. Second, in order to detect facial feature points, we use AAM. Third, gaze detection accuracy is not degraded according to Z distance based on the normalization of input features by using the features which are obtained in an initial user calibration stage. Experimental results showed that gaze detection error was 1.77 degrees and it was reduced by mouse dragging based on the additional facial movement.

• Nuclear Engineering and Technology
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• v.53 no.1
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• pp.44-60
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• 2021

In this paper, we validate the decay heat calculation capability via a two-step method to analyze spent nuclear fuel (SNF) discharged from pressurized water reactors (PWRs). The calculation method is implemented with a lattice code STREAM and a nodal diffusion code RAST-K. One of the features of this method is the direct consideration of three-dimensional (3D) core simulation conditions with the advantage of a short simulation time. Other features include the prediction of the isotope inventory by Lagrange non-linear interpolation and the use of power history correction factors. The validation is performed with 58 decay heat measurements of 48 fuel assemblies (FAs) discharged from five PWRs operated in Sweden and the United States. These realistic benchmarks cover the discharge burnup range up to 51 GWd/MTU, 23.2 years of cooling time, and spanning an initial uranium enrichment range of 2.100-4.005 wt percent. The SNF analysis capability of STREAM is also employed in the code-to-code comparison. Compared to the measurements, the validation results of the FA calculation with RAST-K are within ±4%, and the pin-wise results are within ±4.3%. This paper successfully demonstrates that the developed decay heat calculation method can perform SNF back-end cycle analyses.

• Korean Journal of Agricultural Science
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• v.47 no.4
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• pp.1029-1037
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• 2020

The machine learning algorithm has been widely used in water-related fields such as water resources, water management, hydrology, atmospheric science, water quality, water level prediction, weather forecasting, water discharge prediction, water quality forecasting, etc. However, water quality prediction studies based on the machine learning algorithm are limited compared to other water-related applications because of the limited water quality data. Most of the previous water quality prediction studies have predicted monthly water quality, which is useful information but not enough from a practical aspect. In this study, we predicted the dissolved oxygen (DO) using recurrent neural network with long short-term memory model recurrent neural network long-short term memory (RNN-LSTM) algorithms with hourly- and daily-datasets. Bugok Bridge in Oncheoncheon, located in Busan, where the data was collected in real time, was selected as the target for the DO prediction. The 10-month (temperature, wind speed, and relative humidity) data were used as time prediction inputs, and the 5-year (temperature, wind speed, relative humidity, and rainfall) data were used as the daily forecast inputs. Missing data were filled by linear interpolation. The prediction model was coded based on TensorFlow, an open-source library developed by Google. The performance of the RNN-LSTM algorithm for the hourly- or daily-based water quality prediction was tested and analyzed. Research results showed that the hourly data for the water quality is useful for machine learning, and the RNN-LSTM algorithm has potential to be used for hourly- or daily-based water quality forecasting.

• Journal of the Korean Society of Propulsion Engineers
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• v.25 no.6
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• pp.1-11
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• 2021

To develop an efficient procedure related to the flamelet library, the machine learning process based on artificial neural network(ANN) is applied for the gaseous hydrogen/liquid oxygen combustor under a supercritical pressure condition. For hidden layers, 25 combinations based on Rectified Linear Unit(ReLU) and hyperbolic tangent are adopted to find an optimum architecture in terms of the computational efficiency and the training performance. For activation functions, the hyperbolic tangent is proper to get the high learning performance for accurate properties. A transformation learning data is proposed to improve the training performance. When the optimal node is arranged for the 4 hidden layers, it is found to be the most efficient in terms of training performance and computational cost. Compared to the interpolation procedure, the ANN procedure reduces computational time and system memory by 37% and 99.98%, respectively.