• Journal of Preventive Medicine and Public Health
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• v.33 no.1
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• pp.51-55
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• 2000

Objectives . In large-scale field trials, randomization by cluster is frequently used because of the administrative convenience, a desire to reduce the effect of treatment contamination, and the need to avoid ethical issues that might of otherwise arise. Cluster randomization trials are experiments in which intact social unit, e.g., families, schools, cities, rather than independent individuals are randomly allocated to intervention groups. The positive correlation among responses of subjects from the same cluster is in matter in cluster randomization. This thesis is to compare the results of three randomization methods by standard error of estimator of treatment effect. Methods : We simulated cholesterol data varing the size of the cluster and the level of the correlation in clusters and analyzed the effect of cholesterol-lowering agent. Results : In intra-cluster randomization the standard error of the estimator of treatment effect is smallest relative to that in inter-cluster randomization and that in individual randomization. Conclusions : Infra-cluster randomization is the most efficient in its standard error of estimator of treatment effect but other factor should be considered when selecting a specific randomization method.

• The Korean Journal of Applied Statistics
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• v.22 no.2
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• pp.355-364
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• 2009

A simple method is proposed for constructing nonparametric confidence intervals for the difference or ratio of two median failure times. The method applies when clustered survival data with censoring is randomized either (I) under cluster randomization or (II) subunit randomization. This method is simple to calculate and is based on non-parametric density estimation. The proposed method is illustrated with the otology study data and HL-A antigen study data. Moreover, the simulation results are reported for practical sample sizes.

• Nutrition Research and Practice
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• v.17 no.4
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• pp.789-802
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• 2023

BACKGROUND/OBJECTIVES: Habitual coffee consumption was inversely associated with type 2 diabetes (T2D) and hyperglycemia in observational studies, but the causality of the association remains uncertain. This study tested a causal association of genetically predicted coffee consumption with T2D using the Mendelian randomization (MR) method. SUBJECTS/METHODS: We used five single-nucleotide polymorphisms (SNPs) as instrumental variables (IVs) associated with habitual coffee consumption in a previous genome-wide association study among Koreans. We analyzed the associations between IVs and T2D, fasting blood glucose (FBG), 2h-postprandial glucose (2h-PG), and glycated haemoglobin (HbA1C) levels. The MR results were further evaluated by standard sensitivity tests for possible pleiotropism. RESULTS: MR analysis revealed that increased genetically predicted coffee consumption was associated with a reduced prevalence of T2D; ORs per one-unit increment of log-transformed cup per day of coffee consumption ranged from 0.75 (0.62-0.90) for the weighted mode-based method to 0.79 (0.62-0.99) for Wald ratio estimator. We also used the inverse-variance-weighted method, weighted median-based method, MR-Egger method, and MR-PRESSO method. Similarly, genetically predicted coffee consumption was inversely associated with FBG and 2h-PG levels but not with HbA1c. Sensitivity measures gave similar results without evidence of pleiotropy. CONCLUSIONS: A genetic predisposition to habitual coffee consumption was inversely associated with T2D prevalence and lower levels of FBG and 2h-PG profiles. Our study warrants further exploration.

• Journal of the Korea Society of Computer and Information
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• v.21 no.5
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• pp.79-89
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• 2016

In this paper, we proposed the object classification method using genetic and dynamic random forest consisting of optimal combination of unit tree. The random forest can ensure good generalization performance in combination of large amount of trees by assigning the randomization to the training samples and feature selection, etc. allocated to the decision tree as an ensemble classification model which combines with the unit decision tree based on the bagging. However, the random forest is composed of unit trees randomly, so it can show the excellent classification performance only when the sufficient amounts of trees are combined. There is no quantitative measurement method for the number of trees, and there is no choice but to repeat random tree structure continuously. The proposed algorithm is composed of random forest with a combination of optimal tree while maintaining the generalization performance of random forest. To achieve this, the problem of improving the classification performance was assigned to the optimization problem which found the optimal tree combination. For this end, the genetic algorithm methodology was applied. As a result of experiment, we had found out that the proposed algorithm could improve about 3~5% of classification performance in specific cases like common database and self infrared database compare with the existing random forest. In addition, we had shown that the optimal tree combination was decided at 55~60% level from the maximum trees.

• Journal of the Korea Society of Computer and Information
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• v.22 no.10
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• pp.83-92
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• 2017

Reconnaissance is performed gathering information from a series of scanning probes where the objective is to identify attributes of target hosts. Network reconnaissance of IP addresses and ports is prerequisite to various cyber attacks. In order to increase the attacker's workload and to break the attack kill chain, a few proactive techniques based on the network-based moving target defense (NMTD) paradigm, referred to as IP address mutation/randomization, have been presented. However, there are no commercial or trial systems deployed in real networks. In this paper, we propose a threat model and the request for requirements for developing NMTD techniques. For this purpose, we first examine the challenging problems in the NMTD mechanisms that were proposed for the legacy TCP/IP network. Secondly, we present a threat model in terms of attacker's intelligence, the intended information scope, and the attacker's location. Lastly, we provide seven basic requirements to develop an NMTD mechanism for the legacy TCP/IP network: 1) end-host address mutation, 2) post tracking, 3) address mutation unit, 4) service transparency, 5) name and address access, 6) adaptive defense, and 7) controller operation. We believe that this paper gives some insight into how to design and implement a new NMTD mechanism that would be deployable in real network.

• Journal of Korean Clinical Nursing Research
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• v.18 no.3
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• pp.381-390
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• 2012

Purpose: This study was conducted to examine the effects of simulation-based infection control training on the ICU nurses' perception, clinical performance, and self-efficacy of infection control. Methods: Thirty-eight nurses were assigned into two groups using a career stratified randomization. In the experimental group, the subjects received a simulation-based infection control training, whereas the control group participated in a conventional lecture-based training. Two weeks after the completion of the training sessions, the participants were evaluated for perception, clinical performance, and self-efficacy regarding the infection control. Results: The experimental group that received simulation-based infection control training showed an improvement in perceiving the infection control compared to that of the control group, but the difference was not statistically significant. In terms of the clinical performance, the experimental group and the control group scored $26.05{\pm}3.22$ and $18.53{\pm}3.37$ points respectively, demonstrating a statistical significance (p<.001). There was no significant difference between the two groups in regards to the self-efficacy. Conclusion: The developed simulation-based infection control training showed positive effects in improving clinical performance of infection control over conventional lecture-based training, confirming that a simulation-based training is an effective method in advancing the practical performance of ICU nurses.

• Korean Journal of Radiology
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• v.22 no.2
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• pp.179-188
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• 2021

Objective: This study aimed to prospectively compare the efficacy, safety, and mid-term outcomes of dual-switching monopolar (DSM) radiofrequency ablation (RFA) to those of conventional single-switching monopolar (SSM) RFA in the treatment of hepatocellular carcinoma (HCC). Materials and Methods: This single-center, two-arm, parallel-group, randomized controlled study was approved by the Institutional Review Board. Written informed consent was obtained from all patients upon enrollment. A total of 80 patients with 94 HCC nodules were randomized into either the DSM-RFA group or SSM-RFA group in a 1:1 ratio, using a blocked randomization method (block size 2). The primary endpoint was the minimum diameter of the ablation zone per unit time. The secondary endpoints included other technical parameters, complication rate, technique efficacy, and 2-year clinical outcomes. Results: Significantly higher ablation energy per unit time was delivered to the DSM-RFA group than to the SSM-RFA group (1.7 ± 0.2 kcal/min vs. 1.2 ± 0.3 kcal/min; p < 0.001). However, no significant differences were observed between the two groups for the analyzed variables, including primary endpoint, regarding size of the ablation zone and ablation time. Major complication rates were 4.9% in the DSM-RFA group and 2.6% in the SSM-RFA group (p = 1.000). The 2-year local tumor progression (LTP) rates of the HCC nodules treated using DSM-RFA and SSM-RFA were 8.5% and 4.7%, respectively (p = 0.316). The 2-year LTP-free survival rates of patients in the DSM-RFA and SSM-RFA groups were 90.0% and 94.4%, respectively (p = 0.331), and the 2-year recurrence-free survival rates were 54.9% and 75.7%, respectively (p = 0.265). Conclusion: Although DSM-RFA using a separable clustered electrode delivers higher ablation energy than SSM-RFA, its effectiveness failed to show superiority over SSM-RFA in the treatment of HCC.

• Korean Journal of Applied Biomechanics
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• v.25 no.3
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• pp.343-351
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• 2015

Objective : The purpose of this study was to investigate the effects in the muscle function following 8-week dead-lift training with Whole-body Vibration(WBV) in rehabilitation for sports players. Method : Twenty young sports players. Each subjects were randomly assigned to a resistance training with Whole-body vibration group(TG, n=10), a resistance training without Whole-body vibration group(CG, N=10). The measurements which physical fitness test and joint torque test were performed before the randomization and after the 4-week and 8-week. The WBV group performed the dynamic Dead-lift exercise on a vibration platform during one minute. The CG group performed the equal training without vibration. The WBV and CON group repeated 5 set and trained two times weekly for 8-weeks. Paired t-test was used to test for differences between the groups at baseline and after 4-weeks and 8-Weeks. And independent t-test was used to test for differences between the groups at TG and CG. All analyses were executed using SPSS software 18.0. The level of significance was set at p<.050. Results : Following the 8-Weeks training sessions, an increase in the back-muscle strength was found to be greater for the TG compared with the CG group(p<.05). Muscle endurance was significantly decreased after training than before training only for the CG(p<.05). Isometric Hip/Lumber Extension/Flextion measurement was found to be significantly greater for the TG compared with the CG group(p<.05). The finding indicates that WBV effects as an efficient training stimulus to enhance muscle function by facilitating neural control trail. Following muscle activation in motor unit synchronization of the co-contraction of the muscles. Conclusion : The results imply that the WBV training may have enhanced muscle function in rehabilitation for sports players.