• Journal of Convergence for Information Technology
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• v.12 no.1
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• pp.31-38
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• 2022

This paper applies an expert independent unsupervised neural network learning-based multivariate time series data analysis model, MSCRED(Multi-Scale Convolutional Recurrent Encoder-Decoder), and to overcome the limitation, because the MCRED is based on Auto-encoder model, that train data must not to be contaminated, by using learning data sampling technique, called Subset Sampling Validation. By using the vibration data of power plant equipment that has been labeled, the classification performance of MSCRED is evaluated with the Anomaly Score in many cases, 1) the abnormal data is mixed with the training data 2) when the abnormal data is removed from the training data in case 1. Through this, this paper presents an expert-independent anomaly diagnosis framework that is strong against error data, and presents a concise and accurate solution in various fields of multivariate time series data.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.24 no.12
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• pp.138-146
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• 2010

On wind turbine generators, the speed and volume of the wind affect the turbine angle speed which finally determines the output level of the electric power. However it is very difficult to forecast correctly the future power output and quality based on previous fixed sampling methods. This paper proposes a variable sampling method based on Buneman frequency estimation algorithm to reflect the variations of the frequency and amplitude on wind power outputs. The proposed method is also verified through the performance test by comparing with the results from previous fixed sampling methods and the real measurement data.

• ETRI Journal
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• v.33 no.3
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• pp.326-334
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• 2011

This paper outlines the time jitter effect of a sampling clock on a software-defined radio technology-based digital intermediate frequency (IF) transceiver for a mobile communication base station. The implemented digital IF transceiver is reconfigurable to high-speed data packet access (HSDPA) and three bandwidth profiles: 1.75 MHz, 3.5 MHz, and 7 MHz, each incorporating the IEEE 802.16d worldwide interoperability for microwave access (WiMAX) standard. This paper examines the relationship between the signal-to-noise ratio (SNR) characteristics of a digital IF transceiver with an under-sampling scheme and the sampling jitter effect on a multichannel orthogonal frequency-division multiplexing (OFDM) signal. The simulation and experimental results show that the SNR of the OFDM system with narrower band profiles is more susceptible to sampling clock jitter than systems with relatively wider band profiles. Further, for systems with a comparable bandwidth, HSDPA outperforms WiMAX, for example, a 5 dB error vector magnitude improvement at 15 picoseconds time jitter for a bandwidth of WiMAX 3.5 MHz profile.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.45 no.6
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• pp.34-51
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• 2008

Today, the Internet is a part of our life. For that reason, we regard revealing characteristics of Internet traffic as an important research theme. However, Internet traffic cannot be easily manipulated because it usually occupy huge capacity. This problem is a serious obstacle to analyze Internet traffic. Many researchers use various sampling techniques to reduce capacity of Internet traffic. In this paper, we compare several famous sampling techniques, and propose efficient sampling scheme. We chose some sampling techniques such as Systematic Sampling, Simple Random Sampling and Stratified Sampling with some sampling intensities such as 1/10, 1/100 and 1/1000. Our observation focused on Traffic Volume, Entropy Analysis and Packet Size Analysis. Both the simple random sampling and the count-based systematic sampling is proper to general case. On the other hand, time-based systematic sampling exhibits relatively bad results. The stratified sampling on Transport Layer Protocols, e.g.. TCP, UDP and so on, shows superior results. Our analysis results suggest that efficient sampling techniques satisfactorily maintain variation of traffic stream according to time change. The entropy analysis endures various sampling techniques well and fits detecting anomalous traffic. We found that a traffic volume diminishment caused by bottleneck could induce wrong results on the entropy analysis. We discovered that Packet Size Distribution perfectly tolerate any packet sampling techniques and intensities.

• Communications for Statistical Applications and Methods
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• v.17 no.1
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• pp.89-98
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• 2010

In this paper, a two-stage group sampling plan based on the time truncated life test is proposed for the Weibull distribution. The design parameters such as the number of groups and the acceptance number in each stage are determined by satisfying the producer's and consumer's risks simultaneously when the group size and the test duration are specified. The acceptable reliability level is expressed by the ratio of the true mean life to the specified life. It was demonstrated from the comparison with single-stage group sampling plans that the proposed plan can reduce the average sample number or improve the operating characteristics.

• International Journal of Control, Automation, and Systems
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• v.5 no.5
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• pp.515-525
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• 2007

In this paper, we develop a co-design methodology of stochastic optimal controllers and network parameters that optimizes the overall quality of control (QoC) in networked control systems (NCSs). A new dynamic model for NCSs is provided. The relationship between the system stability and performance and the sampling frequency is investigated, and the analysis of co-design of control and network parameters is presented to determine the working range of the sampling frequency in an NCS. This optimal sampling frequency range is derived based on the system dynamics and the network characteristics such as data rate, time-delay upper bound, data-packet size, and device processing time. With the optimal sampling frequency, stochastic optimal controllers are designed to improve the overall QoC in an NCS. This co-design methodology is a useful rule of thumb to choose the network and control parameters for NCS implementation. The feasibility and effectiveness of this co-design methodology is verified experimentally by our NCS test bed, a ball magnetic-levitation (maglev) system.

• Journal of the Institute of Convergence Signal Processing
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• v.24 no.1
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• pp.51-56
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• 2023

This study investigates the effect of sEMG sampling frequency on CNN learning performance at Korean finger number recognition application. Since the bigger sampling frequency of sEMG signals generates bigger size of input data and takes longer CNN's learning time. It makes making real-time system implementation more difficult and more costly. Thus, there might be appropriate sampling frequency when collecting sEMG signals. To this end, this work choose five different sampling frequencies which are 1,024Hz, 512Hz, 256Hz, 128Hz and 64Hz and investigates CNN learning performance with sEMG data taken at each sampling frequency. The comparative study shows that all CNN recognized Korean finger number one to five at the accuracy of 100% and CNN with sEMG signals collected at 256Hz sampling frequency takes the shortest learning time to reach the epoch at which korean finger number gestures are recognized at the accuracy of 100%.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.23 no.4
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• pp.341-347
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• 2013

Objectives: The aim of this study is to investigate the differences in airborne TDI concentrations based on the filter collection method and liquid collection method and to compare airborne TDIs concentrations by sampling method change when using the filter collection method in the spray-painting process. Methods: For the sample measurement, the filter collection method(OSHA#42) and liquid collection method(NIOSH#5522) were used; for the sampling method, the full-period single sampling and full-period consecutive sampling methods were used. The samples were collected in spray-painting and drying process locations. Results: In all samples collected from the spray-painting and drying process locations through the filter collection and liquid collection methods, greater amounts of 2,6-TDI than 2,4-TDI were detected. When the TDI collection concentrations based on the sampling methods were compared, the concentrations of 2,4-TDI and 2,6-TDI collected by the consecutive sampling method were higher than the concentrations of 2,4-TDI and 2,6-TDI collected by the single sampling method for both the filter collection method and liquid collection method used in the spray-painting process. These differences were statistically significant. Conclusions: When TDI collection concentrations based on the sample measurement methods were compared, the concentration of 2,4-TDI and 2,6-TDI collected through the liquid collection method were higher than the concentrations of 2,4-TDI and 2,6-TDI collected by the filter collection method, and the differences were statistically significant. In the drying process, no difference was shown in the collection concentrations of 2,4-TDI and 2,6-TDI with the two measurement methods.

• Journal of Korean Institute of Industrial Engineers
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• v.39 no.5
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• pp.422-428
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• 2013

In many cases, an $\bar{X}$ control chart which is based on the performance variable is used in industrial fields. However, if the performance variable is too costly or impossible to measure and a less expensive surrogate variable is available, the process may be more efficiently controlled using surrogate variables. In this paper, we propose a model for the economic design of a VSI (Variable Sampling Interval) $\bar{X}$ control chart using a surrogate variable that is linearly correlated with the performance variable. The total average profit model is constructed, which involves the profit per cycle time, the cost of sampling and testing, the cost of detecting and eliminating an assignable cause, and the cost associated with production during out-of-control state. The VSI $\bar{X}$ control charts using surrogate variables are expected to be superior to the Shewhart FSI (Fixed Sampling Interval) $\bar{X}$ control charts using surrogate variables with respect to the expected profit per unit cycle time from economic viewpoint.

• Journal of Information Technology Services
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• v.16 no.3
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• pp.103-111
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• 2017

The real time scheduling is a key research area in high performance computing and has been a source of challenging problems. A periodic task is an infinite sequence of task instance where each job of a task comes in a regular period. The RMS (Rate Monotonic Scheduling) algorithm has the advantage of a strong theoretical foundation and holds out the promise of reducing the need for exhaustive testing of the scheduling. Many real-time systems built in the past based their scheduling on the Cyclic Executive Model because it produces predictable schedules which facilitate exhaustive testing. In this work we propose hybrid scheduling method which combines features of both of these scheduling algorithms. The original rate monotonic scheduling algorithm didn't consider the uniform sampling tasks in the real time systems. We have enumerated some issues when the RMS is applied to our hybrid scheduling method. We found the scheduling bound for the hard real-time systems which include the uniform sampling tasks. The suggested hybrid scheduling algorithm turns out to have some advantages from the point of view of the real time system designer, and is particularly useful in the context of large critical systems. Our algorithm can be useful for real time system designer who must guarantee the hard real time tasks.