• 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.

• Journal of the Chungcheong Mathematical Society
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• v.21 no.4
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• pp.573-583
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• 2008

In this paper, we introduce the techniques of estimating the probability of failure in reliability analysis. The basic idea of each technique is explained and drawbacks of these techniques are examined.

• Smart Structures and Systems
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• v.17 no.4
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• pp.647-667
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• 2016

In this paper, dynamic displacement is estimated with high accuracy by blending high-sampling rate acceleration data with low-sampling rate displacement measurement using a two-stage Kalman estimator. In Stage 1, the two-stage Kalman estimator first approximates dynamic displacement. Then, the estimator in Stage 2 estimates a bias with high accuracy and refines the displacement estimate from Stage 1. In the previous Kalman filter based displacement techniques, the estimation accuracy can deteriorate due to (1) the discontinuities produced when the estimate is adjusted by displacement measurement and (2) slow convergence at the beginning of estimation. To resolve these drawbacks, the previous techniques adopt smoothing techniques, which involve additional future measurements in the estimation. However, the smoothing techniques require more computational time and resources and hamper real-time estimation. The proposed technique addresses the drawbacks of the previous techniques without smoothing. The performance of the proposed technique is verified under various dynamic loading, sampling rate and noise level conditions via a series of numerical simulations and experiments. Its performance is also compared with those of the existing Kalman filter based techniques.

• Journal of applied mathematics & informatics
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• v.42 no.1
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• pp.179-187
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• 2024

In the Quality Control and inspection processes, the use of attribute sampling strategies is crucial. In this study, we incorporate the neutrosophic fuzzy acceptance sampling plan method to present a fresh approach to attribute sampling plans. Utilizing the benefits of neutrosophic fuzzy sets, the proposed sampling plan method models and assesses the acceptance standards for attribute sampling. We compare the suggested method to already-in-use attribute sampling techniques plans with new attribute six sigma sampling techniques plan is proposed in order to verified its efficacy. The outcomes show the neutrosophic fuzzy acceptance sampling plan's superiority in terms of its capacity to manage uncertainties, account for ambiguity, and produce more precise quality evaluation outputs.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.10 no.2
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• pp.49-55
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• 1992

Sampling techniques is very important in digital elevation model. There are scanning and digitizing method of sampling techniques. This study is limited in digitizing method. Continous sampling method use contour lines as same entity and grid method is a direct reading of sample elevation in each grid. Triangulated irregular method is needed to identity topographical lines to sample elevation data. As a results, authors know that continous sampling method has economic in input system and triangulated irregular method has a small memory size.

• Nuclear Engineering and Technology
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• v.49 no.6
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• pp.1172-1180
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• 2017

The application of Monte Carlo (MC) to large-scale fixed-source problems has recently become possible with new hybrid methods that automate generation of parameters for variance reduction techniques. Two common variance reduction techniques, weight windows and source biasing, have been automated and popularized by the consistent adjoint-driven importance sampling (CADIS) method. This method uses the adjoint solution from an inexpensive deterministic calculation to define a consistent set of weight windows and source particles for a subsequent MC calculation. One of the motivations for source consistency is to avoid the splitting or rouletting of particles at birth, which requires computational resources. However, it is not always possible or desirable to implement such consistency, which results in inconsistent source biasing. This paper develops an original framework that mathematically expresses the coupling of the weight window and source biasing techniques, allowing the authors to explore the impact of inconsistent source sampling on the variance of MC results. A numerical experiment supports this new framework and suggests that certain classes of problems may be relatively insensitive to inconsistent source sampling schemes with moderate levels of splitting and rouletting.

• 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.

• Journal of Environmental Health Sciences
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• v.26 no.3
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• pp.50-54
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• 2000

Ventilation rates can be measured directly by a tracer decay method, although little is known of the effects of different sampling intervals on decay rte calculations. This study determined variations in decay rates calculated by three techniques using residential ozone decay data. The calculation techniques were a regression technique, decay techniques using half-life and average-life, and finite difference techniques using two different time intervals. Variation associated with regression technique calculations for residential ozone decay rates based on data from both sample intervals were within 10% (2.81$\pm$1.88 hr-1). However, both half-life and finite difference technique calculations using a shorter-time interval were significantly different from those obtained with the regression technique(p<0.05). Therefore, the use of short sampling intervals in tracer decay may cause significant error in decay rate calculations.

• Journal of the Korea Safety Management & Science
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• v.8 no.5
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• pp.243-251
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• 2006

This paper is to propose various quality and reliability sampling inspection methods to perform the competitive global outsourcing strategy while purchasing and subcontracting. The study also represents implementation strategy which can be efficiently and effectively used in the enterprise. Quality sampling inspection schemes extend reliability inspection techniques with a little change.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.9B
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• pp.1795-1805
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• 1999

In an OFDM (Orthogonal Frequency-Division Multiplexing) system, the sampling frequency offset between the transmitter and receiver is known to cause the interchannel interference (ICI), resulting in performance degradation. In this paper, we propose two time-domain techniques to estimate the sampling frequency offset, especially for a high data-rate OFDM system. The first technique estimates the sampling frequency offset by using the phase difference between two received samples with a fixed amount of time interval, corresponding to the transmitted training symbol, under the assumption of perfect symbol and carrier offset synchronization. The second technique estimates the sampling frequency offset and carrier frequency offset jointly, when the two offsets exist together, by using two training symbols with different frequency components and using a sample algebraic calculation. The proposed estimation techniques for sampling frequency offset cause no time delay due to all time-domain processing, and have a good performance due to no ICI effect. The performances of the proposed techniques are demonstrated by various simulations.