• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.7
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• pp.3217-3238
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• 2018

In this paper, a depth image up-sampling method is put forward by using pixel classifying and jointed bilateral filtering. By analyzing the edge maps originated from the high-resolution color image and low-resolution depth map respectively, pixels in up-sampled depth maps can be classified into four categories: edge points, edge-neighbor points, texture points and smooth points. First, joint bilateral up-sampling (JBU) method is used to generate an initial up-sampling depth image. Then, for each pixel category, different refinement methods are employed to modify the initial up-sampling depth image. Experimental results show that the proposed algorithm can reduce the blurring artifact with lower bad pixel rate (BPR).

• Nuclear Engineering and Technology
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• v.48 no.2
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• pp.376-385
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• 2016

A hexagonally arrayed 37-pin wire-wrapped rod bundle has been chosen to provide the experimental data of the pressure loss and flow rate in subchannels for validating subchannel analysis codes for the sodium-cooled fast reactor core thermal/hydraulic design. The iso-kinetic sampling method has been adopted to measure the flow rate at subchannels, and newly designed sampling probes which preserve the flow area of subchannels have been devised. Experimental tests have been performed at 20-115% of the nominal flow rate and $60^{\circ}C$ (equivalent to Re ~ 37,100) at the inlet of the test rig. The pressure loss data in three measured subchannels were almost identical regardless of the subchannel locations. The flow rate at each type of subchannel was identified and the flow split factors were evaluated from the measured data. The predicted correlations and the computational fluid dynamics results agreed reasonably with the experimental data.

• Proceedings of the Korean Statistical Society Conference
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• 2005.05a
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• pp.191-196
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• 2005

Knowing the time of the process change could lead to quicker identification of the responsible special cause and less process down time, and it could help to reduce the probability of incorrectly identifying the special cause. In this paper, we propose a MLE of the process change point when control charts with the fixed sampling rate (FSR) scheme or the variable sampling rate (VSR) scheme monitor a process to detect changes in the process mean and/or variance of a normal quality variable.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.12C
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• pp.1249-1256
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• 2006

This paper proposes, based on a bandpass sampling theory, a novel method to find valid sampling frequency range and minimum sampling rate with low computational complexity for downconversion of multiple bandpass radio frequency (RF) signals. Guard-bands or spacing between adjacent downconverted signal spectrums are also taken into consideration in determining sampling frequency for practical implementation. Moreover, we verify through comparison with other method that the proposed method has more advantageous properties.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.8
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• pp.849-853
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• 2014

In micro-scale electromechanical systems, the power to perform accurate position sensing often greatly exceeds the power needed to generate motion. This paper explores the implications of sampling rate and amplifier noise density selection on the performance of a system identification algorithm using a capacitive sensing circuit. Specific performance objectives are to minimize or limit convergence rate and power consumption to identify the dynamics of a rotary micro-stage. A rearrangement of the conventional recursive least-squares identification algorithm is performed to make operating cost an explicit function of sensor design parameters. It is observed that there is a strong dependence of convergence rate and error on the sampling rate, while energy dependence is driven by error that may be tolerated in the final identified parameters.

• The KIPS Transactions:PartC
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• v.11C no.6 s.95
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• pp.711-718
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• 2004

Packet sampling is the techniques to collect a part of the packets through network and analyze the characteristicsof the traffic for managing the network and keeping security. This paper presents a study on the sampling techniques applied to DDoS traffic and on the characteristics of the sampled traffic to detect DDoS attack efficiently and improve traffic analysis capacity. Three famous sampling techniques are evaluated with different sampling rates on various DDoS traffics. To analyze traffic characteristics, one of the DDoS attack detection method. Traffic Rate Analysis (TRA) is used. Simulation results verify that using sampling techniques preserve the traffic characteristics of DDoS and do not significantly reduce the detection accuracy.

• The Korean Journal of Applied Statistics
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• v.28 no.3
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• pp.495-509
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• 2015

We study a classification problem of significant differences in the proportion of two groups known as the unbalanced classification problem. It is usually more difficult to classify classes accurately in unbalanced data than balanced data. Most observations are likely to be classified to the bigger group if we apply classification methods to the unbalanced data because it can minimize the misclassification loss. However, this smaller group is misclassified as the larger group problem that can cause a bigger loss in most real applications. We compare several classification methods for the unbalanced data using sampling techniques (up and down sampling). We also check the total loss of different classification methods when the asymmetric loss is applied to simulated and real data. We use the misclassification rate, G-mean, ROC and AUC (area under the curve) for the performance comparison.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.4
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• pp.279-285
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• 2007

The objective of the research is two fold. The first is to design and propose a stable and robust learning control algorithm. The controller is CMAC Learning Controller which consists of a model-based controller, such as LQR or PID, as a reference control and a CMAC. The second objective is to implement a reference control and CMAC at two different sampling rates. Generally, a conventional controller is designed based on a mathematical plant model. However, increasing complexity of the plant and accuracy requirement on mathematical models nearly prohibits the application of the conventional controller design approach. To avoid inherent complexity and unavoidable uncertainty in modeling, biology mimetic methods have been developed. One of such attempts is Cerebellar Model Articulation Computer(CMAC) developed by Albus. CMAC has two main disadvantages. The first disadvantage of CMAC is increasing memory requirement with increasing number of input variables and with increasing accuracy demand. The memory needs can be solved with cheap memories due to recent development of new memory technology. The second disadvantage is a demand for processing powers which could be an obstacle especially when CMAC should be implemented in real-time. To overcome the disadvantages of CMAC, we propose CMAC learning controller with multiple sampling rates. With this approach a conventional controller which is a reference to CMAC at high enough sampling rate but CMAC runs at the processor's unoccupied time. To show efficiency of the proposed method, an inverted pendulum controller is designed and implemented. We also demonstrate it's possibility as an industrial control solution and robustness against a modeling uncertainty.

• Proceedings of the KOSOMBE Conference
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• v.1992 no.05
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• pp.79-81
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• 1992

This paper describes the design of an adaptive closed circuit anesthesia controller based on a multiplexed mass spectrometer system. The controller deals with measurement deterioration caused by measurement delay and rise time through a tong catheter as well as long sampling times due to the multiplexed measurements. Measurement data is extrapolated between sampling periods to increase the estimation convergence rate. A multiple-step-ahead predictive control algorithm is used to calculate intermediatc control inputs between sampling intervals. Simulations are used to validate the designed controller.

• Journal of Korean Society for Quality Management
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• v.30 no.1
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• pp.74-96
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• 2002

The objectives of this study is to suggest the rectifying sampling inspection plan considering quality cost. Limiting quality level(LQL) plans(also called LTPD plans) and outgoing quality(OQ) plans are considered. The Hald's linear cost model is discussed with and without a beta prior for the distribution of the fraction of nonconforming items in a lot. It is assumed that the sampling inspection is error free. We consider the design of reliability acceptance sampling plan (RASP) for failure rate level qualification at selected confidence level. The lifetime distribution of products is assumed to be exponential. MIL-STD-690C and K C 6032 standards provide this procedures. But these procedures have some questions to apply in the field. The cost of test and confidence level(1-$\beta$ risk) are the problem between supplier and user. So, we suggest that the optimal life test sampling inspection plans using simple linear cost model considering product cost, capability of environment chamber, environmental test cost, and etc. Especially, we consider a reliability of lots that contain some nonconforming items. In this case we assumed that a nonconforming item fail after environmental life test. Finally, we develope the algorithm of the optimal sampling inspection plan based on minimum costs for rectifying inspection and RASP. And computer application programs are developed So, it is shown how the desired sampling plan can be easily found.