• Journal of Environmental Impact Assessment
• /
• v.20 no.6
• /
• pp.879-890
• /
• 2011

The GOSAT (Greenhouse gases Observing SATellite) data provide new opportunities the most regionally complete and up-to-date assessment of $CO_2$. However, in practice, GOSAT records often suffer from missing data values mainly due to unfavorable meteorological condition in specific time periods of data acquisition. The aim of this research was to identify optimal spatial interpolation techniques to ensure the continuity of $CO_2$ from samples taken in the North East Asia. The accuracy among ordinary kriging (OK), universal kriging (UK) and simple kriging (SK) was compared based on the combined consideration of $R^2$ values, Root Mean Square Error (RMSE), Mean Error (ME) for variogram models. Cross validation for 1312 random sampling points indicate that the (UK) kriging is the best geostatistical method for spatial predictions of $CO_2$ in the East Asia region. The results from this study can be useful for selecting optimal kriging algorithm to produce $CO_2$ map of various landscapes. Also, data users may benefit from a statistical approach that would allow them to better understand the uncertainty and limitations of the GOSAT sample data.

• Journal of Broadcast Engineering
• /
• v.19 no.2
• /
• pp.227-239
• /
• 2014

This paper proposes an enhance prediction for conventional near-lossless coder to effectively lower external memory bandwidth in image processing SoC. First, we utilize an already reconstructed green component as a base of predictor of the other color component because high correlation between RGB color components usually exists. Next, we can improve prediction performance by applying variable block size prediction. Lastly, we use minimum internal memory and improve a temporal prediction performance by using a template dictionary that is sampled in previous frame. Experimental results show that the proposed algorithm shows better performance than the previous works. Natural images have approximately 30% improvement in coding efficiency and CG images have 60% improvement on average.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2012.05a
• /
• pp.289-290
• /
• 2012

This paper propose the distance measurement algorithms using the 3-axis accelermeter sensor. This algorithms is based on the human gait charateristic. The proposed algorithms used the sampling data from the 3-axis accelermeter sensor. We improved the error rate as less than eight-percent compare the real movement distance with measured distance to apply the threshold value and the additional value according to the change of the acceleration value.

• 제어로봇시스템학회:학술대회논문집
• /
• 2003.10a
• /
• pp.1684-1688
• /
• 2003

In this paper, position and speed control algorithm of LSM (Linear Stepping Motor) using general-purpose PCI I/O board is discussed. The main purpose of this paper is to show that LSM controller can be established on the non real time operating system such as Microsoft Win2000 under the assumption that thread priority strategy is well designed. We can guarantee sampling interval less than 5msec based on the Pentium III microprocessor. Therefore this kind of LSM controller development environment makes shorten the prior research period needed to verify the validness of the proposed control strategy. We also introduce the tool of the real-time windows target system of matlab, which also makes shorten the prior research period. The main focus of this paper is on developing general purpose NT device driver which can drive the general purpose PCI board and applying it for implementing the hardware interface for 2- axis linear stepping motor control. From the experimental results show that the developed LSM controller guarantee 2 micrometer resolution in position control with 10cm/sec moving speed

• Smart Structures and Systems
• /
• v.14 no.6
• /
• pp.1269-1289
• /
• 2014

With the sub-stepping technique, the numerical analysis in real-time dynamic hybrid testing is split into the response analysis and signal generation tasks. Two target computers that operate in real-time may be assigned to implement these two tasks, respectively, for fully extending the simulation scale of the numerical substructure. In this case, the integration time-step of solving the dynamic response of the numerical substructure can be dozens of times bigger than the sampling time-step of the controller. The time delay between the real and desired feedback forces becomes more striking, which challenges the well-developed delay compensation methods in real-time dynamic hybrid testing. This paper focuses on displacement prediction and force correction for delay compensation in the real-time dynamic hybrid testing with a large integration time-step. A new displacement prediction scheme is proposed based on recently-developed explicit integration algorithms and compared with several commonly-used prediction procedures. The evaluation of its prediction accuracy is carried out theoretically, numerically and experimentally. Results indicate that the accuracy and effectiveness of the proposed prediction method are of significance.

• Journal of KIISE:Computer Systems and Theory
• /
• v.29 no.8
• /
• pp.463-471
• /
• 2002

In order to implement virtual endoscopy, high-speed rendering algorithm that generates accurate perspective projection images and efficient collision detection method are essential. In this paper we propose an efficient virtual endoscopy system based on volume rendering technique. It is possible to skip over empty (transparent) space using the distance value produced in preprocessing time, and it does not deteriorate image quality since it is an extension of ray-casting. It also accelerates rendering speed with minimal loss of image quality by adjusting sampling interval along a ray according to direction of the ray. Using the distance information, we can simplify the collision detection of volumetric objects.

• Journal of Broadcast Engineering
• /
• v.9 no.1
• /
• pp.54-63
• /
• 2004

A new motion compensated frame Interpolation (MCI) algorithm by block based motion estimation (BME) is proposed. The block for the BME is composed of a large overlapped block for practical object motion estimation (ME) and a small block (which has a coinciding center with the ME-block) for the more precise motion compensated image description. Pixels in the block for the ME are sub-sampled to reduce computational complexity. The proposed method is executed with the various ME-blocks which have different size and sub-sampling ratio, and compared to the conventional method.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
• /
• v.20 no.1
• /
• pp.100-106
• /
• 2009

This paper deals with an estimation problem of the gain and phase imbalances between the in-phase and quadrature components in the quadrature receivers which are widely used in wireless communications. It is shown that the estimates derived from the suggested auto-calibration algorithm is asymptotically minimum-variance unbiased as a function of the sampling time. In order to show this characteristic, the probability density functions of the estimates for the gain and phase imbalances are derived first. Then the mean and variance functions are investigated analytically or numerically based on the density functions.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.13 no.4
• /
• pp.91-98
• /
• 2017

Previous works for detecting arrhythmia have mostly used nonlinear method such as artificial neural network, fuzzy theory, support vector machine to increase classification accuracy. Most methods require higher computational cost and larger processing time. Therefore it is necessary to design efficient algorithm that classifies PVC(premature ventricular contraction) and decreases computational cost by accurately detecting minimal feature point based on only R peak through optimal R wave. We propose an optimal R wave detection and PVC classification method through extracting minimal feature point in IoT environment. For this purpose, we detected R wave through optimal threshold value and extracted RR interval and R peak pattern from noise-free ECG signal through the preprocessing method. Also, we classified PVC in realtime through RR interval and R peak pattern. The performance of R wave detection and PVC classification is evaluated by using record of MIT-BIH arrhythmia database. The achieved scores indicate the average of 99.758% in R wave detection and the rate of 93.94% in PVC classification.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.67 no.11
• /
• pp.1562-1569
• /
• 2018

Sensor readings always have a certain degree of randomness and fuzziness due to its intrinsic property, other electronic devices in the circuitry, wires and the rapidly changing environment. In an electrical control system, such readings will bring instability in the system and other undesired events especially if the signal hovers around the threshold. This paper proposes a Gaussian-based statistical approach in stabilizing the output through sampling the sensor data and automatic tuning the threshold to the range of multiple standard deviations. It takes advantage of the Central limit theorem and its properties assuming that a large number of sensor data samples will eventually converge to a Gaussian distribution. Experimental results demonstrate the effectiveness of the proposed algorithm in completely stabilizing the outputs over known filtering algorithms like Exponential smoothing and Kalman Filter.