• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.6
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• pp.2139-2151
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• 2014

Embedded system testing, especially long-term reliability testing, of flash memory solutions such as embedded multi-media card, secure digital card and solid-state drive involves strategic decision making related to test sample size to achieve high test coverage. The test sample size is the number of flash memory devices used in a test. Earlier, there were physical limitations on the testing period and the number of test devices that could be used. Hence, decisions regarding the sample size depended on the experience of human testers owing to the absence of well-defined standards. Moreover, a lack of understanding of the importance of the sample size resulted in field defects due to unexpected user scenarios. In worst cases, users finally detected these defects after several years. In this paper, we propose that a large number of potential field defects can be detected if an adequately large test sample size is used to target weak features during long-term reliability testing of flash memory solutions. In general, a larger test sample size yields better results. However, owing to the limited availability of physical resources, there is a limit on the test sample size that can be used. In this paper, we address this problem by proposing a self-adaptive reliability testing scheme to decide the sample size for effective long-term reliability testing.

• Physical Therapy Korea
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• v.23 no.2
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• pp.93-99
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• 2016

Background: Parametric statistical procedures are typically conducted under the condition in which a sample distribution is statistically identical with its population. In reality, investigators use inferential statistics to estimate parameters based on the sample drawn because population distributions are unknown. The uncertainty of limited data from the sample such as lack of sample size may be a challenge in most rehabilitation studies. Objects: The purpose of this study is to review the bootstrapping method to overcome shortcomings of limited sample size in rehabilitation studies. Methods: Articles were reviewed. Results: Bootstrapping method is a statistical procedure that permits the iterative re-sampling with replacement from a sample when the population distribution is unknown. This statistical procedure is to enhance the representativeness of the population being studied and to determine estimates of the parameters when sample size are too limited to generalize the study outcome to target population. The bootstrapping method would overcome limitations such as type II error resulting from small sample sizes. An application on a typical data of a study represented how to deal with challenges of estimating a parameter from small sample size and enhance the uncertainty with optimal confidence intervals and levels. Conclusion: Bootstrapping method may be an effective statistical procedure reducing the standard error of population parameters under the condition requiring both acceptable confidence intervals and confidence level (i.e., p=.05).

• Genomics & Informatics
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• v.10 no.2
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• pp.117-122
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• 2012

A sample size with sufficient statistical power is critical to the success of genetic association studies to detect causal genes of human complex diseases. Genome-wide association studies require much larger sample sizes to achieve an adequate statistical power. We estimated the statistical power with increasing numbers of markers analyzed and compared the sample sizes that were required in case-control studies and case-parent studies. We computed the effective sample size and statistical power using Genetic Power Calculator. An analysis using a larger number of markers requires a larger sample size. Testing a single-nucleotide polymorphism (SNP) marker requires 248 cases, while testing 500,000 SNPs and 1 million markers requires 1,206 cases and 1,255 cases, respectively, under the assumption of an odds ratio of 2, 5% disease prevalence, 5% minor allele frequency, complete linkage disequilibrium (LD), 1:1 case/control ratio, and a 5% error rate in an allelic test. Under a dominant model, a smaller sample size is required to achieve 80% power than other genetic models. We found that a much lower sample size was required with a strong effect size, common SNP, and increased LD. In addition, studying a common disease in a case-control study of a 1:4 case-control ratio is one way to achieve higher statistical power. We also found that case-parent studies require more samples than case-control studies. Although we have not covered all plausible cases in study design, the estimates of sample size and statistical power computed under various assumptions in this study may be useful to determine the sample size in designing a population-based genetic association study.

• Journal of Korean Academy of Nursing
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• v.27 no.4
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• pp.857-870
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• 1997

The purposes of this study were to describe 12 years of patient-related oncology nursing research in Korea, identifying various nursing interventions, and assesing the effectiveness of the interventions, through analysis and synthesis of the accumulated research papers. One hundred and seventy-nine studies were selected for this study and these were mostly descriptive in design (69.2%). Of the 179 studies, 25 met the criteria for meta-analytic treatment. Twenty-five experimental studies were found in theses and dissertations (68%), 92% used convenience sample, and the median sample size was 40. Subjects were predominantly in treatment and rehabilitation (76%). Most studies(68%) were not derived from a theory base, with only 8% reporting use of a nursing theory. Results of the meta-analysis are as follows. The effect size of the nursing intervention type was found to be significantly effective. The standardized mean difference ranged from a high positive of 2.55 to a low negative of -0.22. Direct personal nursing intervention method was more effective than indirect group method. Two nursing intervention methods were more effective than one. The greatest effect size was thyxical intervention. The greatest mean effect size was scalp hypothermia technique. Teaching was a frequent intervention after 1990, although a wide range of treatments were studied. Effect size of intervention for symptom management was largest in relieving pain. Effective intervention method for relieving anxiety was exercise.

• Communications for Statistical Applications and Methods
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• v.22 no.5
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• pp.519-530
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• 2015

The geometric chart has proven more effective than Shewhart p or np charts to monitor the proportion nonconforming in high-quality processes. Implementing a geometric chart commonly requires the assumption that the in-control proportion nonconforming is known or accurately estimated. However, accurate parameter estimation is very difficult and may require a larger sample size than that available in practice in high-quality process where the proportion of nonconforming items is very small. Thus, the error in the parameter estimation increases and may lead to deterioration in the performance of the control chart if a sample size is inadequate. We suggest adjusting the control limits in order to improve the performance when a sample size is insufficient to estimate the parameter. We propose a linear function for the adjustment constant, which is a function of the sample size, the number of nonconforming items in a sample, and the false alarm rate. We also compare the performance of the geometric charts without and with adjustment using the expected value of the average run length (ARL) and the standard deviation of the ARL (SDARL).

• Communications for Statistical Applications and Methods
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• v.27 no.3
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• pp.301-311
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• 2020

Schwarz's Bayesian information criterion (BIC) is one of the most popular criteria for model selection, that was derived under the assumption of independent and identical distribution. For correlated data in longitudinal studies, Jones (Statistics in Medicine, 30, 3050-3056, 2011) modified the BIC to select the best linear mixed effects model based on the effective sample size where the number of parameters in covariance structure was not considered. In this paper, we propose an extended Jones' modified BIC by considering covariance parameters. We conducted simulation studies under a variety of parameter configurations for linear mixed effects models. Our simulation study indicates that our proposed BIC performs better in model selection than Schwarz's BIC and Jones' modified BIC do in most scenarios. We also illustrate an example of smoking data using a longitudinal cohort of cancer patients.

• Journal of Korean Medicine Rehabilitation
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• v.15 no.2
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• pp.117-117
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• 2005

Objectives : This experimental study was designed to investigate the effect of SBY-III extract on the weight, cell size of epididymal fat-pad, fat accumulation area in liver, serum lipid level and UCP1 mRNA in brown adipose tissue of high fat diet-fed obese rats continued by high fat diet and regulated by normal Diet. Methods : The body weight gain, weight of the internal organs(epididymis, liver, brown adipose tissue), insulin, triglyceride, total cholesterol, total lopod, free fatty acid, expression of UCP1 mRNA were measured in high fat diet-fed obese rats continued by high fat diet and regulated by normal diet. The experimental study are divided into exp-I and exp-II. Each study was administered normal diet, high fat diet and SBY-III according to each situation. Normal group is normal diet for 8 weeks. Exp-I are divided into control group(high fat diet for 8 weeks) and sample group(high fat diet for 8 weeks and SBY-III for last 2 weeks). Exp-II are divided into control group(high fat diet for 6 weeks and normal diet for 2 weeks) and sample group(high fat diet for 6 weeks and normal diet with SBY-III for 2 weeks). These were then compared mutually. Results : 1. Irrespective of diet control, sample group taken SBY-III showed the more effective decrease of weight gain than control group and diet control-fed sample group with SBY-III showed the more effective decrease of weight loss including weight gain than control group. 2. Irrespective of diet control, sample group taken SBY-III showed the more effective decrease cell size of epididymal fat-pad, fat accumulation area in liver than control group. 3. Non diet control-fed sample group taken SBY-III showed the more effective decrease of serum triglyceride, total lipid, free fatty acid than control group and diet control-fed sample group taken SBY-III showed the decrease of serum triglyceride, free fatty acid than control group. 4. Only diet control-fed sample group taken SBY-III showed the decrease of UCP1 volume. Conclusions : These results shows that SBY-III has effects on anti-obesity, especially keeping pace with diet control.

• Advances in nano research
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• v.7 no.2
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• pp.125-134
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• 2019

The Origanum vulgare L.-mediated synthesis of Ag nanoparticles was successfully realized within the present study. Various concentrations of the $AgNO_3$ used as a silver precursor (1, 2.5, 5, 10 and 100 mM) were used. Very rapid formation of Ag nanoparticles was observed, as only minutes were necessary for the completion of the reaction. With the increasing concentration, red shift of the surface plasmon resonance peak was observed in the Vis spectra. According to photon cross-correlation spectroscopy results, the finest grain size distribution was obtained for the 2.5 mM sample. The transmission electron microscopy analysis of this sample has shown bimodal size distribution with larger crystallites with 100 nm size and smaller around 10 nm. The antibacterial activity was also the best for this sample so the positive correlation between good grain size distribution and antibacterial activity was found. The in-depth discussion of antibacterial activity with related works from the materials science point of view is provided, namely emphasizing the role of effective nanoparticles distribution within the plant extract or matrix. The antibacterial activity seems to be governed by both content of Ag nanoparticles and their effective distribution. This work contributes to still expanding environmentally acceptable field of green synthesis of silver nanoparticles.

• Geomechanics and Engineering
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• v.14 no.2
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• pp.151-159
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• 2018

Annually, the global production of construction aggregates reaches over 40 billion tons, making aggregates the largest mining sector by volume and value. Currently, the aggregate industry is shifting from sand to hard rock as a result of legislation limiting the extraction of natural sands and gravels. A major implication of this change in the aggregate industry is the need for understanding rock fragmentation and energy absorption to produce more cost-effective aggregates. In this paper, we focused on incorporating dynamic rock and soil mechanics to understand the effects of loading rate and water saturation on the rock fragmentation and energy absorption of three different sandstones (Red, Berea and Buff) with different pore sizes. Rock core samples were prepared in accordance to the ASTM standards for compressive strength testing. Saturated and dry samples were subsequently prepared and fragmented via fast and dynamic compressive strength tests. The particle size distributions of the resulting fragments were subsequently analyzed using mechanical gradation tests. Our results indicate that the rock fragment size generally decreased with increasing loading rate and water content. In addition, the fragment sizes in the larger pore size sample (Buff sandstone) were relatively smaller those in the smaller pore size sample (Red sandstone). Notably, energy absorption decreased with increased loading rate, water content and rock pore size. These results support the conclusion that rock fragment size is positively correlated with the energy absorption of rocks. In addition, the rock fragment size increases as the energy absorption increases. Thus, our data provide insightful information for improving cost-effective aggregate production methods.

• Communications for Statistical Applications and Methods
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• v.9 no.3
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• pp.693-701
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• 2002

When the lowest dose level compared with zero-dose control has significant difference in effect, it is referred as minimum effective dose (MED). In this paper, we discuss several nonparametric methods for finding MED using updated rank at each sequential test step in small sample size and suggest new nonparametric procedures based on placement. Monte Carlo Simulation is adapted to compare power and Familywise Error Rate(FWE) of the new procedures with those of discussed nonparametric tests for finding MED.