• Nuclear Engineering and Technology
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• v.52 no.6
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• pp.1148-1155
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• 2020

This work presents two different methods for quantifying and propagating the uncertainty associated with fuel composition at end of life for cask criticality calculations. The first approach, the computational approach uses parametric uncertainty including those associated with nuclear data, fuel geometry, material composition, and plant operation to perform forward depletion on Monte-Carlo sampled inputs. These uncertainties are based on experimental and prior experience in criticality safety. The second approach, the data-driven approach relies on using radiochemcial assay data to derive code bias information. The code bias data is used to perturb the isotopic inventory in the data-driven approach. For both approaches, the uncertainty in k_eff for the cask is propagated by performing forward criticality calculations on sampled inputs using the distributions obtained from each approach. It is found that the data driven approach yielded a higher uncertainty than the computational approach by about 500 pcm. An exploration is also done to see if considering correlation between isotopes at end of life affects k_eff uncertainty, and the results demonstrate an effect of about 100 pcm.

• Journal of Environmental Science International
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• v.11 no.12
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• pp.1195-1204
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• 2002

We calculated dose rate using radiative transfer equations to consider radiative processes distinctly. The dose rate at Pohang(36°02'N, 129°23'E) was calculated using measured ozone and meteorological data and two-stream approximations(quadrature, Eddington, delta Eddington, PIFM(practical improved flux method), discrete ordinate, delta discrete ordinate) are used in solving equation. The purpose of this study is to determine the most compatible radiative transfer approximation for simulating the radiative and photochemical processes of atmosphere through comparision between calculated and measured values. Dose rate of the biologically effective irradiance in the region 0.28-0.32 U m showed the highest value when quadrature and Eddington was used and lower value on condition that delta scaling was applied. Correlation coefficient between dose rate at surface using radiation transfer equation and measured UV-B at Pohang was 0.78, 0.79 and 0.81 when delta Eddington, PIFM and delta discrete ordinate were used. Also, in case of above approximations were used, MBE(Mean Bias Error) was within -0.3MED/30min and RMBE(Relative Mean Bias Error) was below 10% between 1200 LST and 1400 LST Approximations which are compatible in estimating radiative process are delta Eddington, PIFM and delta discrete ordinate. Especially, in case that radiative process is considered more detail, delta discrete ordinate increased the number of stream is proper.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.13
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• pp.5161-5166
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• 2014

Our aim was to access the association between recreational physical activity (RPA) and risk of ovarian cancer (OC). The studies were retrieved from the PubMed and Embase databases up to February 20th, 2014. Risk ratios (OR) and 95% confidence intervals (CI) were used to estimate effect sizes. Random-effects or fixed-effects models were used to pool the data. The trim and fill method was applied for sensitivity analysis. Begg's rank correlation test and Egger's regression asymmetry test were employed to assess the publication bias. A total of 6 studies (435398 participants including 2983 OC patients) were included in this meta-analysis. The overall estimate indicated that there was weakly inverse association between RPA and OC risk (RR=0.90, 95%CI: 0.72-1.12, p=0.335). Meanwhile, for prospective cohort studies, a result consistent with the overall estimate was obtained (RR=1.12, 95% CI: 0.88-1.42, p=0.356). However, for case control studies, the pooled estimate of RR was 0.76 (95%CI: 0.64-0.90, p=0.002), indicating a clear significant association between RPA and OC risk. In addition, the sensitivity analysis indicated a significant link between RPA and risk of OC after removing Lahmann's study (RR=0.80, 95% CI: 0.68-0.93, p=0.004). No significant publication bias was found (Begg's test: p=1.00; Egger's test: p=0.817). In conclusion, our meta-analysis indicated a weakly inverse relationship between RPA and the occurrence of OC.

• KCID journal
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• v.19 no.1
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• pp.87-96
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• 2012

Information of local solar radiation is essential for many field, including water resources management, crop yield estimation, crop growth model, solar energy systems and irrigation and drainage design. Unfortunately, solar radiation measurements are not easily available due to the cost and maintenance and calibration requirements of the measuring equipment and station. Therefore, it is important to elaborate methods to estimate the solar radiation based on readily available meteorological data. In this study, two empirical equations are employed to estimate daily solar radiation using Cheongju Regional Meteorological Office data. Two scenarios are considered: (a) sunshine duration data are available for a given location, or (b) only daily cloudiness index records exist. Simple linear regression with daily sunshine duration and cloudiness index as the dependent variable accounted for 91% and 80%, respectively of the variation of solar radiation(H) at 2011. Daily global solar radiation is highly correlated with sunshine duration. In order to indicate the performance of the models, the statistical test methods of the mean bias error(MBE), root mean square error(RMSE) and correlation coefficient(r) are used. Sunshine duration and cloudiness index can be easily and reliably measured and data are widely available.

• Journal of Microbiology and Biotechnology
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• v.26 no.11
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• pp.1972-1982
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• 2016

Influenza A virus is a single-stranded RNA virus with a genome of negative polarity. Owing to the antigenic diversity and cross concrete shift, an immense number of novel strains have developed astronomically over the years. The present work deals with the codon utilization partialness among five different influenza A viruses isolated from human hosts. All the subtypes showed the homogeneous pattern of nucleotide utilization with a little variation in their utilization frequencies. A lower bias in codon utilization was observed in all the subtypes as reflected by higher magnitudes of an efficacious number of codons. Dinucleotide analysis showed very low CpG utilization and a high predilection of A/T-ending codons. The H5N1 subtype showed noticeable deviation from the rest. Codon pair context analysis showed remarkable depletion of NNC-GNN and NNT-ANN contexts. The findings alluded towards GC-compositional partialness playing a vital role, which is reflected in the consequential positive correlation between the GC contents at different codon positions. Untangling the codon utilization profile would significantly contribute to identifying novel drug targets that will pacify the search for antivirals against this virus.

• Journal of Environmental Science International
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• v.27 no.7
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• pp.499-507
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• 2018

Agricultural meteorological information is an important resource that affects farmers' income, food security, and agricultural conditions. Thus, such data are used in various fields that are responsible for planning, enforcing, and evaluating agricultural policies. The meteorological information obtained from automatic weather observation systems operated by rural development agencies contains missing values owing to temporary mechanical or communication deficiencies. It is known that missing values lead to reduction in the reliability and validity of the model. In this study, the hierarchical Bayesian spatio-temporal model suggests replacements for missing values because the meteorological information includes spatio-temporal correlation. The prior distribution is very important in the Bayesian approach. However, we found a problem where the spatial decay parameter was not converged through the trace plot. A suitable spatial decay parameter, estimated on the bias of root-mean-square error (RMSE), which was determined to be the difference between the predicted and observed values. The latitude, longitude, and altitude were considered as covariates. The estimated spatial decay parameters were 0.041 and 0.039, for the spatio-temporal model with latitude and longitude and for latitude, longitude, and altitude, respectively. The posterior distributions were stable after the spatial decay parameter was fixed. root mean square error (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE), and bias were calculated for model validation. Finally, the missing values were generated using the independent Gaussian process model.

• The Korean Journal of Applied Statistics
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• v.34 no.2
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• pp.177-190
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• 2021

Random forests is a popular method that improves the instability and accuracy of decision trees by ensembles. In contrast to increasing the accuracy, the ease of interpretation is sacrificed; hence, to compensate for this, variable importance is provided. The variable importance indicates which variable plays a role more importantly in constructing the random forests. However, when a predictor is correlated with other predictors, the variable importance of the existing importance algorithm may be distorted. The downward bias of correlated predictors may reduce the importance of truly important predictors. We propose a new algorithm remedying the downward bias of correlated predictors. The performance of the proposed algorithm is demonstrated by the simulated data and illustrated by the real data.

• The Journal of Industrial Distribution & Business
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• v.13 no.8
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• pp.1-7
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• 2022

Purpose: The present study concentrates on the issues that affected the employees directly and acted as stress factors. These stress factors affect how the employees perform while undertaking their duties. Furthermore, this study evaluated how the involvement of the corporate counsel affected the company by enhancing the productivity of the employees. Research design, data and methodology: The research design of this research is a literature content analysis and method for data handling should be described, and the resultant combination of the studies should include the consistency measures for every meta-analysis. Specify any risk assessment of bias that may impact the cumulative evidence, such as the publication bias and the selective reporting within studies. Results: The finding shows that change in the location of employees' organizational restructuring and the introduction of new technologies also contributed to significant organizational stress factors. These results show a substantial correlation between the magnitude of the adjustments' effects on employees' performance. Conclusions: The current study strongly concludes that counselors, through their prowess, can analyze and evaluate the stress factors that are evident among the employees and in the organization. Some of these factors may be office layout, organizational codes of ethics, organization rules, and employees' personal challenges.

• Corrosion Science and Technology
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• v.22 no.3
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• pp.153-163
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• 2023

Two types of accelerated tests, Water Drop Test (WDT) and Temperature-Humidity-Bias Test (THBT), can be used to evaluate the susceptibility to electrochemical migration (ECM). In the WDT, liquid water is directly applied to a specimen, typically a patterned conductor like a printed circuit board. Time to failure in the WDT typically ranges from several seconds to several minutes. On the other hand, the THBT is conducted under elevated temperature and humidity conditions, allowing for assessment of design and life cycle factors on ECM. THBT is widely recognized as a more suitable method for reliability testing than WDT. In both test methods, localized corrosion can be observed on the anode. Composition of dendrites formed during the WDT is similar to that formed during THBT. However, there is a lack of correlation between the time to failure obtained from WDT and that obtained from THBT. In this study, we investigated the relationship between electrochemical parameters and time to failure obtained from both WDT and THBT. Differences in time to failure can be attributed to actual anode potential obtained in the two tests.

• Atmosphere
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• v.17 no.1
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• pp.55-68
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• 2007

Future climate changes over East Asia are projected by anthropogenic forcing of greenhouse gases and aerosols using ECHO-G/S (ECHAM4/HOPE-G). Climate simulation in the 21st century is conducted with three standard SRES scenarios (A1B, B1, and A2) and the model performance is assessed by the 20th Century (20C3M) experiment. From the present climate simulation (20C3M), the model reproduced reliable climate state in the most fields, however, cold bias in temperature and dry bias of summer in precipitation occurred. The intercomparison among models using Taylor diagram indicates that ECHO-G/S exhibits smaller mean bias and higher pattern correlation than other nine AOGCMs. Based on SRES scenarios, East Asia will experience warmer and wetter climate in the coming 21st century. Changes of geographical patterns from the present to the future are considerably similar through all the scenarios except for the magnitude difference. The temperature in winter and precipitation in summer show remarkable increase. In spite of the large uncertainty in simulating precipitation by regional scale, we found that the summer (winter) precipitation at eastern coast (north of $40^{\circ}N$) of East Asia has significantly increased. In the 21st century, the warming over the continents of East Asia showed much more increase than that over the ocean. Hence, more enhanced (weakened) land-sea thermal contrast over East Asia in summer (winter) will cause strong (weak) monsoon. In summer, the low pressure located in East Asia becomes deeper and the moisture from the south or southeast is transported more into the land. These result in increasing precipitation amount over East Asia, especially at the coastal region. In winter, the increase (decrease) of precipitation is accompanied by strengthening (weakening) of baroclinicity over the land (sea) of East Asia.