• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.1B
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• pp.86-100
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• 2004

To provide the end-to-end service differentiation for assured services, the random early demotion and promotion (REDP) marker in the edge router at each domain boundary monitors the aggregate flow of the incoming in-profile packets and demotes in-profile packets or promotes the previously demoted in-profile packets at the aggregate flow level according to the negotiated interdomain service level agreement (SLA). The REDP marker achieves UDP fairness in demoting and promoting packets through random and early marking decisions on packets. But, TCP fairness of the REDP marker is not obvious as for UDP sources. In this paper, to improve TCP fairness of the REDP marker, we propose a modified REDP marker where we combine a dropper, meters and a token filling rate configuration component with the REDP marker. To make packet transmission rates of TCP flows more fair, at the aggregate flow level the combined dropper drops incoming excessive in-profile packets randomly with a constant probability when the token level in the leaky bucket stays in demotion region without incoming demoted in-profile packets. Considering the case where the token level cannot stay in demotion region without the prior demotion, we propose a token filling rate configuration method using traffic meters. By using the token filling rate configuration method, the modified REDP marker newly configures a token filling rate which is less than the negotiated rate determined by interdomain SLA and larger than the current input aggregate in-profile traffic rate. Then, with the newly configured token filling rate, the token level in the modified REDP marker can stay in demotion region pertinently fir the operation of the dropper to improve TCP fairness. We experiment with the modified REDP marker using ns2 simulator fur TCP sources at the general case where the token level cannot stay in demotion region without the prior demotion at the negotiated rate set as the bottleneck link bandwidth. The simulation results demonstrate that through the combined dropper with the newly configured token filling rate, the modified REDP marker also increases both aggregate in-profile throughput and link utilization in addition to TCP fairness improvement compared to the REDP marker.

• Journal of Dental Anesthesia and Pain Medicine
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• v.20 no.1
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• pp.29-37
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• 2020

Background: This study evaluated the efficacy of three intraoral topical anesthetics in reducing the injection needle prick pain from local anesthetic among children aged 7-11 years old. Methods: It is a prospective, Interventional, parallel design, single-blind, randomized clinical trial in which subjects (n=90) aged 7-11 years were included in the study based on an inclusion criteria. Subjects were divided into three groups based on computer-generated randomization with an allocation ratio of 1:1:1. Groups A, B, and C received benzocaine 20% jelly (Mucopain gel, ICPA health products Ltd, Ankleshwar, India), cetacaine anesthetic liquid (Cetylite Industries, Inc, Pennsauken, NJ), and EMLA cream (2% AstraZeneca UK Ltd, Luton, UK), respectively, according to manufacturer's instructions, for 1 minute prior to local anesthetic injection. After application of topical anesthetic agent, for all the groups, baseline pre-operative (prior to topical anesthetic administration) and post-operative scores (after local anesthetic administration) of pulse rate was recorded using Pulse oximeter (Gibson, Fingertip Pulse Oximeter, MD300C29, Beijing Choice Electronic). Peri-operative (i.e., during the administration of local anesthesia) scores were recorded using Face, Legs, Activity, Cry, Consolability (FLACC) Scale, Modified Children hospital of Eastern Ontario Pain Scale (CPS) behavior rating scale, and Faces Pain Scale (FPS-R) - Revised (For self-reported pain). Direct self-reported and physiological measures were ascertained using FPS-R - Revised and Pulse oximeter, respectively, whereas CPS and FLACC scales assessed behavioral measures. To test the mean difference between the three groups, a one way ANOVA with post hoc tests was used. For statistical significance, a two-tailed probability value of P < 0.05 was considered as significant. Results: The Cetacaine group had significantly lower pain scores for self-report (P < 0.001), behavioral, and physiological measures (P < 0.001) than the other two groups. However, there was no significant difference between the Benzocaine group and EMLA group during palatal injection prick. Conclusion: Cetacaine can be considered as an effective topical anesthetic agent compared to benzocaine 20% jelly (Mucopain gel) and EMLA cream.

• Journal of Applied Reliability
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• v.17 no.3
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• pp.213-223
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• 2017

Purpose: The purpose of this study is to arrange the life data analysis literatures based on the Bayesian method quantitatively and provide it as tables. Methods: The Bayesian method produces a more accurate estimates of other traditional methods in a small sample size, and it requires specific algorithm and prior information. Based on these three characteristics of the Bayesian method, the criteria for classifying the literature were taken into account. Results: In many studies, there are comparisons of estimation methods for the Bayesian method and maximum likelihood estimation (MLE), and sample size was greater than 10 and not more than 25. In probability distributions, a variety of distributions were found in addition to the distributions of Weibull commonly used in life data analysis, and MCMC and Lindley's Approximation were used evenly. Finally, Gamma, Uniform, Jeffrey and extension of Jeffrey distributions were evenly used as prior information. Conclusion: To verify the characteristics of the Bayesian method which are more superior to other methods in a smaller sample size, studies in less than 10 samples should be carried out. Also, comparative study is required by various distributions, thereby providing guidelines necessary.

• Geophysics and Geophysical Exploration
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• v.5 no.4
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• pp.262-271
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• 2002

This study presents a practical procedure for the Bayesian inversion of geophysical data. We have applied geostatistical techniques for the acquisition of prior model information, then the Markov Chain Monte Carlo (MCMC) method was adopted to infer the characteristics of the marginal distributions of model parameters. For the Bayesian inversion of dipole-dipole array resistivity data, we have used the indicator kriging and simulation techniques to generate cumulative density functions from Schlumberger array resistivity data and well logging data, and obtained prior information by cokriging and simulations from covariogram models. The indicator approach makes it possible to incorporate non-parametric information into the probabilistic density function. We have also adopted the MCMC approach, based on Gibbs sampling, to examine the characteristics of a posteriori probability density function and the marginal distribution of each parameter.

• Journal of the Korea institute for structural maintenance and inspection
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• v.14 no.5
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• pp.119-127
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• 2010

This paper provides a new approach for durability prediction of reinforced concrete structures exposed to carbonation. In this method, the prediction can be updated successively by a Bayes' theorem when additional data are available. The stochastic properties of model parameters are explicitly taken into account in the model. To simplify the procedure of the model, the probability of the durability limit is determined based on the samples obtained from the Latin Hypercube Sampling(LHS) technique. The new method may be very useful in design of important concrete structures and help to predict the remaining service life of existing concrete structures which have been monitored. For using the new method, in which the prior distribution is developed to represent the uncertainties of the carbonation velocity using data of concrete structures(3700 specimens) in Korea and the likelihood function is used to monitor in-situ data. The posterior distribution is obtained by combining a prior distribution and a likelihood function. Efficiency of the LHS technique for simulation was confirmed through a comparison between the LHS and the Monte Calro Simulation(MCS) technique.

• Journal of Environmental Impact Assessment
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• v.24 no.3
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• pp.260-277
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• 2015

The object of this study was the climate change sensitivity assessment of Korean Fir and Khinghan Fir as a representative subalpine plant in South Korea. Using species distribution models, we predicted the probability of current and future species distribution. According to this study, potential distribution that have been predicted based on the threshold (MTSS) is, Khinghan Fir was higher loss rate than Korean Fir. And in the climate change sensitivity assessment using the scalar sensitivity weight ($W_{is}$), $W_{is}$ of Korean Fir was higher relatively than the sensitivity of Khinghan Fir. When using the species distribution models as shown in this study may vary depending on the probability of presence data and spatial variables. Therefore should be prior decision studies on the ecological environment of the study species. Based on this study, if it is domestic applicable climate change sensitivity assessment method is developed. it would be important decision-making to climate change and biological diversity of adaptation policy.

• Journal of Electrical Engineering and Technology
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• v.12 no.2
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• pp.689-700
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• 2017

This paper presents an effective approach for wind turbine (WT) condition assessment based on the data collected from wind farm supervisory control and data acquisition (SCADA) system. Three types of assessment indices are determined based on the monitoring parameters obtained from the SCADA system. Neural Networks (NNs) are used to establish prediction models for the assessment indices that are dependent on environmental conditions such as ambient temperature and wind speed. An abnormal level index (ALI) is defined to quantify the abnormal level of the proposed indices. Prediction errors of the prediction models follow a normal distribution. Thus, the ALIs can be calculated based on the probability density function of normal distribution. For other assessment indices, the ALIs are calculated by the nonparametric estimation based cumulative probability density function. A Back-Propagation NN (BPNN) algorithm is used for the overall WT condition assessment. The inputs to the BPNN are the ALIs of the proposed indices. The network structure and the number of nodes in the hidden layer are carefully chosen when the BPNN model is being trained. The condition assessment method has been used for real 1.5 MW WTs with doubly fed induction generators. Results show that the proposed assessment method could effectively predict the change of operating conditions prior to fault occurrences and provide early alarming of the developing faults of WTs.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.10a
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• pp.103-112
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• 1996

Optimal pricing research in general has been focused on profit maximizing strategy under the given product life-time T. Here we have tried to study the effect of uncertain product life-time on dynamic optimal pricing strategy. In reality, the life-time of product is more likely to be uncertain and not known as well. In terms of approximating the model to the concerned reality, so-called model validity, it seems to be more desirable to consider the uncertainty of product life-time into the optimal pricing strategy model, For this purpose, we tried two different approaches. One is to consider diverse product life-time probability functions under fixed life-time T. In this case, we might have the same product life-time as the previous study, but the process could be different in the expectation of product's discontinuity. The other is that life-time itself is not determined and thus it is the situation in which we can only decide optimal price on incremental basis. The former is the situation in which although we got some strong guess on life-time of a certain product, the pattern of expected life-time probability could be different. The question is what could be optimal pricing strategies on such different product life-time situations. But since in the latter, we don't assume any idea on the life-time of product. proper optimal pricing could be derived only from the past prices and diffusion information. While the latter seems to be safer in the aspect of model assumption, the former could be more realistic because we might have more or less a prior knowledge on the product life-time itself.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.7B
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• pp.711-721
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• 2004

To provide the end-to-end service differentiation for assured services, the random early demotion and promotion (REDP) marker in the edge router at each domain boundary monitors the aggregate flow of the incoming in-profile packets and demotes in-profile packets or promotes the previously demoted in-profile packets at the aggregate flow level according to the negotiated interdomain service level agreement (SLA). The REDP marker achieves UDP fairness in demoting and promoting packets through random and early marking decisions on packets. But, TCP fairness of the REDP marker is not obvious as fur UDP sources. In this paper, to improve TCP fairness of the REDP marker, we combine a dropper with the REDP marker. To make packet transmission rates of TCP flows more fair, at the aggregate flow level the combined dropper drops incoming excessive in-profile packets randomly with a constant probability when the token level in the leaky bucket stays In demotion region without incoming demoted in-profile packets. It performs a dropping in the demotion at a domain boundary only if there is no prior demotion. The concatenate dropping at multiple domains is avoided to manifest the effect of a dropping at a domain boundary on TCP fairness. We experiment with the REDP marker with the combined dropper using ns2 simulator for TCP sources. The simulation results show that the REDP marker with the combined dropper improves TCP fairness in demoting and promoting packets by generating fair demoted in-profile traffic compared to the REDP marker. The effectiveness of the selected drop probability is also investigated with showing its impact on the performance of the REDP marker with the combined dropper.

• The KIPS Transactions:PartC
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• v.11C no.5
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• pp.659-670
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• 2004

Handoff is one of the most important features for the user's mobility in a wireless cellular communication system. It is related to resource reservation at nearby cells. Resource reservation to the new connection point should occur prior to handoff to enable the user to receive the data or services at the new location, at the same level of service as at the previous location. For the efficient resource reservation, mobility prediction has been reported as an effective means to decrease the call dropping probability and to shorten the handoff latency in a wireless cellular environment. A recently proposed algorithm, ZMHB, makes use of the history of the user's positions within the current cell to predict the next cell. But, the prediction of the ZMHB algorithm is found to be 80∼85% accurate for regular and random movements. In this paper, we propose a new improved ZMHB mobility prediction algorithm, which is called Detailed-ZMHB that uses detailed-zone-based tracking of mo-bile users to predict user movements. The effectiveness of the proposed algorithm is then demonstrated through a simulation.