• Journal of Broadcast Engineering
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• v.20 no.4
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• pp.568-579
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• 2015

Recently, mobile devices with touch display panel are widely used. Accuracy and reaction speed of touch signal are very important in touch devices. Therefore, we need to develop an effective algorithm to reduce touch noise quickly and accurately. This paper proposes a touch noise reduction algorithm using Kalman filtering in consideration of signal motion. First, a specific pre-emphasis processing is applied to an input signal so as to maximize the effect of Kalman filtering. In other words, a pure signal in the touch signal increases but noise in the touch signal decreases. Next, motion of the signal is detected. Motion estimation is performed only if motion is detected. If we detect motion by using the only neighborhood of the signal, we can reduce about 75% of the computation in comparison with examining the entire area. Finally, Kalman filtering using the previous state of current signal is performed. Experimental results show that the proposed algorithm suppresses touch noise sufficiently without degradation of the pure signal

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.5
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• pp.1155-1163
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• 2011

In this paper, we propose a new pre-processing algorithm applied to depth map to improve the coding efficiency. Now, 3DV/FTV group in the MPEG is working for standard of 3DVC(3D video coding), but compression method for depth map images are not confirmed yet. In the proposed algorithm, after dividing the histogram distribution of a given depth map by EM clustering method based on GMM, we classify the depth map into several layered images. Then, we apply different mean shift filter to each classified image according to the existence of background or foreground in it. In other words, we try to maximize the coding efficiency while keeping the boundary of each object and taking average operation toward inner field of the boundary. The experiments are performed with many test images and the results show that the proposed algorithm achieves bits reduction of 19% ~ 20% and computation time is also reduced.

• Journal of the Society of Naval Architects of Korea
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• v.55 no.6
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• pp.474-481
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• 2018

This paper is to compare by numerical analysis the flow characteristics and propulsion performance of stern with the shape change of K-duct, a pre-swirl duct developed by Korea Research Institute of Ships & Ocean Engineering (KRISO). First, the characteristics of the propeller and the resistance and self-propulsion before and after the attachment of the K-duct to the ship were verified and the validity of the calculation method was confirmed by comparing this result with the model test results. After that, resistance and self-propulsion calculations were performed by the same numerical method when the K-duct was changed into five different shapes. The efficiency of the other five cases was compared using the delivery horsepower in the model scale and the flow characteristics of the stern were analyzed as the velocity and pressure distributions in the area between the duct end and the propeller plane. For the computation, STAR-CCM +, a general-purpose flow analysis program, was used and the Reynolds Averaged Navier-Stokes (RANS) equations were applied. Rigid Body Motion (RBM) method was used for the propeller rotating motion and SST $k-{\omega}$ turbulence model was applied for the turbulence model. As a result, the tangential velocity of the propeller inflow changed according to the position angle change of the stator, and the pressure of the propeller hub and the cap changes. This regulated the propeller hub vortex. It was confirmed that the vortex of the portion where the fixed blade and the duct meet was reduced by blunt change.

• Journal of Information Processing Systems
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• v.14 no.6
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• pp.1445-1456
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• 2018

Environment perception and three-dimensional (3D) reconstruction tasks are used to provide unmanned ground vehicle (UGV) with driving awareness interfaces. The speed of obstacle segmentation and surrounding terrain reconstruction crucially influences decision making in UGVs. To increase the processing speed of environment information analysis, we develop a CPU-GPU hybrid system of automatic environment perception and 3D terrain reconstruction based on the integration of multiple sensors. The system consists of three functional modules, namely, multi-sensor data collection and pre-processing, environment perception, and 3D reconstruction. To integrate individual datasets collected from different sensors, the pre-processing function registers the sensed LiDAR (light detection and ranging) point clouds, video sequences, and motion information into a global terrain model after filtering redundant and noise data according to the redundancy removal principle. In the environment perception module, the registered discrete points are clustered into ground surface and individual objects by using a ground segmentation method and a connected component labeling algorithm. The estimated ground surface and non-ground objects indicate the terrain to be traversed and obstacles in the environment, thus creating driving awareness. The 3D reconstruction module calibrates the projection matrix between the mounted LiDAR and cameras to map the local point clouds onto the captured video images. Texture meshes and color particle models are used to reconstruct the ground surface and objects of the 3D terrain model, respectively. To accelerate the proposed system, we apply the GPU parallel computation method to implement the applied computer graphics and image processing algorithms in parallel.

• International Journal of Computer Science & Network Security
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• v.21 no.2
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• pp.120-130
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• 2021

The spinal cord or CSF surgery is a very complex process. It requires continuous pre and post-surgery evaluation to have a better ability to diagnose the disease. To detect automatically the suspected areas of tumors and symptoms of CSF leakage during the development of the tumor inside of the brain. We propose a new method based on using computer software that generates statistical results through data gathered during surgeries and operations. We performed statistical computation and data collection through the Google Source for the UK National Cancer Database. The purpose of this study is to address the above problems related to the accuracy of missing hybrid KNN values and finding the distance of tumor in terms of brain cancer or CSF images. This research aims to create a framework that can classify the damaged area of cancer or tumors using high-dimensional image segmentation and Laplace transformation method. A high-dimensional image segmentation method is implemented by software modelling techniques with measures the width, percentage, and size of cells within the brain, as well as enhance the efficiency of the hybrid KNN algorithm and Laplace transformation make it deal the non-zero values in terms of missing values form with the using of Frobenius Matrix for deal the space into non-zero values. Our proposed algorithm takes the longest values of KNN (K = 1-100), which is successfully demonstrated in a 4-dimensional modulation method that monitors the lighting field that can be used in the field of light emission. Conclusion: This approach dramatically improves the efficiency of hybrid KNN method and the detection of tumor region using 4-D segmentation method. The simulation results verified the performance of the proposed method is improved by 92% sensitivity of 60% specificity and 70.50% accuracy respectively.

• Proceedings of the Korean Vacuum Society Conference
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• 2016.02a
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• pp.196.2-196.2
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• 2016

The design and development procedures of SF6 gas circuit breakers are still largely based on trial and error through testing although the development costs go higher every year. The computation cannot cover the testing satisfactorily because all the real processes arc not taken into account. But the knowledge of the arc behavior and the prediction of thermal plasmas inside SF6 interrupters by numerical simulations are more useful than those by experiments due to the difficulties to obtain physical quantities experimentally and the reduction of computational costs in recent years. In this paper, in order to get further information into the interruption process of a SF6 self-blast interrupter, which is based on the combination of thermal expansion and arc rotation, gas flow simulations with a CFD-arc modeling are performed during the whole switching process such as high-current period, pre-current zero period, and current-zero period. Through the complete work, the temperature of residual arcs as well as the breakdown index after current zero should be a good criterion to predict the dielectric capability of interrupters.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.2 no.2
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• pp.133-138
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• 2002

In this paper, we propose an integrated GUI environment of parallel fuzzy inference system fur pattern classification of remote sensing data. In this, as 4 fuzzy variables in condition part and 104 fuzzy rules are used, a real time and parallel approach is required. For frost fuzzy computation, we use the scan line conversion algorithm to convert lines of each fuzzy linguistic term to the closest integer pixels. We design 4 fuzzy processor unit to be operated in parallel by using FPGA. As a GUI environment, PCI transmission, image data pre-processing, integer pixel mapping and fuzzy membership tuning are considered. This system can be used in a pattern classification system requiring a rapid inference time in a real-time.

• Journal of Power Electronics
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• v.16 no.4
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• pp.1306-1315
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• 2016

Modern power systems driven by high-power converters have become inevitable in view of the ever increasing demand for electric power. The total power loss can be reduced by limiting the switching losses in such power converters; increased power efficiency can thus be achieved. A reduced switching frequency that is less than a few hundreds of hertz is applied to power converters that produce output waveforms with high distortion. Selective harmonic elimination pulse width modulation (SHEPWM) is an optimized low switching frequency pulse width modulation method that is based on offline estimation. This method can pre-program the harmonic profile of the output waveform over a range of modulation indices to eliminate low-order harmonics. In this paper, a SHEPWM scheme for three-phase three-leg neutral point clamped inverter is proposed. Aside from eliminating the selected harmonics, the DC capacitor voltages at the DC bus are also balanced because of the symmetrical pulse pattern over a quarter cycle of the period. The technique utilized in the estimation of switching angles involves the firefly algorithm (FA). Compared with other techniques, FA is more robust and entails less computation time. Simulation in the MATLAB/SIMULINK environment and experimental verification in the very large scale integration platform with Spartan 6A DSP are performed to prove the validity of the proposed technique.

• Korea-Australia Rheology Journal
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• v.16 no.3
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• pp.117-128
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• 2004

The effect of molecular parameters on the steady vortex behaviors in the inertial viscoelastic flow past a cylinder has been investigated. FENE-CR model was considered as a constitutive equation. A recently developed iterative solution method (Kim et al., (in press)) was found to be successfully applicable to the computation of inertial viscoelastic flows. The high-resolution computations were carried out to understand the detailed flow behaviors based on the efficient iterative solution method armed with ILU(0) type pre-conditioner and BiCGSTAB method. The discrete elastic viscous split stress-G/streamline upwind Petrov Galerkin (DEVSS-G/SUPG) formulation was adopted as a stabilization method. The vortex size decreased as elasticity increases. However, the vortex enhancement was also observed in the case of large extensibility, which means that the vortex behavior is strongly dependent upon the material parameters. The longitudinal gradient of normal stress was found to retard the formation of vortex, whereas the extensional viscosity played a role in the vortex enhancement. The present results are expected to be helpful for understanding the inertial vortex dynamics of viscoelastic fluids in the flow past a confined cylinder.

• Journal of Electrical Engineering and Technology
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• v.10 no.6
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• pp.2240-2248
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• 2015

The integration of the large-scale wind power brings great challenge to the stability of the power grid. This paper investigates and studies the fault on May 14, 2012 of the large-scale cascading trip-off of wind turbines in North China. According to the characteristics of the voltage variation, the fault process is divided into three stages: the pre-event stage, the critical stage before cascading, and the cascading stage. The scenes in the fault are reproduced, using the full-size actual power system model. Simulation models of double-fed induction generators (DFIGs) and SVCs including protection settings and controller strategies are carefully chosen to find out the reason of voltage instability in each stage. Some voltage dynamic that have never been observed before in the faults of the same kind are analyzed in detail, and an equivalent voltage sensitive dynamic model of DFIG is proposed for the fast computation. The conclusions about the voltage dynamics are validated by the actual PMU observation evidence.