• Journal of Korean Academy of Nursing
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• v.45 no.4
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• pp.501-512
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• 2015

Purpose: The purpose of this study, which was guided by the Resiliency Model of Family Stress, Adjustment, and Adaptation, was twofold: (a) to explore family and parental adaptation and factors influencing family adaptation in Korean families of children with Down syndrome (DS) through a quantitative methodology and (b) to understand the life with a Korean child with DS through a qualitative method. Methods: A mixed-methods design was adopted. A total of 147 parents of children with DS completed a package of questionnaires, and 19 parents participated in the in-depth interviews. Quantitative and qualitative data were analyzed using stepwise multiple regression and content analysis respectively. Results: According to the quantitative data, the overall family adaptation scores indicated average family functioning. Financial status was an important variable in understanding both family and parental adaptation. Family adaptation was best explained by family problem solving and coping communication, condition management ability, and family hardiness. Family strains and family hardiness were the family factors with the most influence on parental adaption. Qualitative data analysis showed that family life with a child with DS encompassed both positive and negative aspects and was expressed with 5 themes, 10 categories, and 16 sub-categories. Conclusion: Results of this study expand our limited knowledge and understanding concerning families of children with DS in Korea and can be used to develop effective interventions to improve the adaptation of family as a unit as well as parental adaptation.

• Communications of Mathematical Education
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• v.28 no.3
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• pp.303-320
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• 2014

The purpose of research is to analyze research trends and methods in a total of 709 studies published in five domestic mathematics education journals issued by Korea Citation Index (KCI) for the last 10 years (2003-2013) and strands in stages of research methods among mixed methods studies. As a result, the majority of articles in the five journals used either qualitative or quantitative methods and mixed methods research was less than 10 % of the total number of studies. The majority of mixed methods was research equally mixing qualitative and quantitative methods. The mixed methods research consisted primarily of quantitative with descriptive statistics and very little qualitative with conceptual framework based on theoretical background. Our results provide not only trends of the current research methods, but also implications for various future research paradigms in mathematics education.

• Korean Journal of Environmental Agriculture
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• v.30 no.4
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• pp.367-376
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• 2011

BACKGROUND: In order to develop effective assessment method for Korean paddy soil microbial community structure, reliable genomic DNA extraction method from paddy soil and quantitative real-time PCR (qRT-PCR) method are needed to establish METHODS AND RESULTS: Out of six conventional soil genomic DNA extraction methods, anion exchange resin purification method was turn to be the most reliable. Various PCR primers for distinguishing five bacterial phylum (${\alpha}$-Proteobacteria, ${\beta}$-Proteobacteria, Actinobacteria, Bacteroidetes, Firmicutes), all bacteria, and all fungi were tested. Various qRT-PCR temperature conditions were also tested by repeating experiment. Finally, both genomic DNA extraction and qRT-PCR methods for paddy soil were well established. CONCLUSION: Quantitative real-time PCR (qRT-PCR) method to assess paddy soil microbial community was established.

• Journal of Preventive Medicine and Public Health
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• v.56 no.1
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• pp.12-20
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• 2023

Quantitative and qualitative research explore various social phenomena using different methods. However, there has been a tendency to treat quantitative studies using complicated statistical techniques as more scientific and superior, whereas relatively few qualitative studies have been conducted in the medical and healthcare fields. This review aimed to provide a proper understanding of qualitative research. This review examined the characteristics of quantitative and qualitative research to help researchers select the appropriate qualitative research methodology. Qualitative research is applicable in following cases: (1) when an exploratory approach is required on a topic that is not well known, (2) when something cannot be explained fully with quantitative research, (3) when it is necessary to newly present a specific view on a research topic that is difficult to explain with existing views, (4) when it is inappropriate to present the rationale or theoretical proposition for designing hypotheses, as in quantitative research, and (5) when conducting research that requires detailed descriptive writing with literary expressions. Qualitative research is conducted in the following order: (1) selection of a research topic and question, (2) selection of a theoretical framework and methods, (3) literature analysis, (4) selection of the research participants and data collection methods, (5) data analysis and description of findings, and (6) research validation. This review can contribute to the more active use of qualitative research in healthcare, and the findings are expected to instill a proper understanding of qualitative research in researchers who review qualitative research reports and papers.

• Communications for Statistical Applications and Methods
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• v.8 no.3
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• pp.753-765
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• 2001

We suggest a quantitative conditional unrelated question model that can be used in obtaining more sensitive information. For whom say "yes" about the less 7han sensitive question .B we ask only about the more sensitive variable X. We extend our model to two sample case when there is no information about the true mean of the unrelated variable Y. Finally we compare the efficiency of our model with that of Greenberg et al.′s.

• Journal of Pharmaceutical Investigation
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• v.15 no.3
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• pp.151-159
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• 1985

For the determination of aliphatic carbamates, the quantitative analysis of carisoprodol was investigated by gab chromatography (GC) and spectrophotometry. All the methods studied were found to be very quantitative. The minimum experimental amounts of GC method, spectrophotometric method I and II were approximately $10^{-9},\;10^{-5}$ and $10^{-8}$ mole, respectively. The obtained results showed that GC method I was much more sensitive and rapid than spectrophotometric method II.

• Industrial Engineering and Management Systems
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• v.14 no.4
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• pp.392-400
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• 2015

Monitoring of plasma etch processes for fault detection is one of the hallmark procedures in semiconductor manufacturing. Optical emission spectroscopy (OES) has been considered as a gold standard for modeling plasma etching processes for on-line diagnosis and monitoring. However, statistical quantitative methods for processing the OES data are still lacking. There is an urgent need for a statistical quantitative method to deal with high-dimensional OES data for improving the quality of etched wafers. Therefore, we propose a robust relevance vector machine (RRVM) for regression with statistical quantitative features for modeling etch rate and uniformity in plasma etch processes by using OES data. For effectively dealing with the OES data complexity, we identify seven statistical features for extraction from raw OES data by reducing the data dimensionality. The experimental results demonstrate that the proposed approach is more suitable for high-accuracy monitoring of plasma etch responses obtained from OES.

• Asian-Australasian Journal of Animal Sciences
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• v.20 no.3
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• pp.453-460
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• 2007

An overview of developments important in the future of animal breeding is discussed. Examples from the application of quantitative genetic principles to selection in chickens and mice are given. Lessons to be learned from these species are that selection for production traits in livestock must also consider selection for reproduction and other fitness-related traits and inbreeding should be minimized. Short-term selection benefits of best linear unbiased predictor methodology must be weighed against long-term risks of increased rate of inbreeding. Different options have been developed to minimize inbreeding rates while maximizing selection response. Development of molecular genetic methods to search for quantitative trait loci provides the opportunity for incorporating marker-assisted selection and introgression as new tools for increasing efficiency of genetic improvement. Theoretical and computer simulation studies indicate that these methods hold great promise once genotyping costs are reduced to make the technology economically feasible. Cloning and transgenesis are not likely to contribute significantly to genetic improvement of livestock production in the near future.

• Bulletin of the Korean Chemical Society
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• v.23 no.3
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• pp.417-422
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• 2002

Comparison studies of the Quantitative Structure Activity Relationship (QSAR) methods with new imidazo-quinolinedione derivatives were conducted using Comparative Molecular Field Analysis (CoMFA), Comparative Molecular Similarity Indices Analysis (CoMSIA), and the Hologram Quantitative Structure Activity Relationship (HQSAR). When the CoMFA crossvalidation value, q2, was 0.625, the Pearson correlation coefficient, r2, was 0.973. In CoMSIA, q2 was 0.52 and r2 was 0.979. In the HQSAR, q2 was 0.501 and r2 was 0.924. The best result was obtained using the CoMSIA method according to a comparison of the calculated values with the real in vitro cytotoxic activities against human ovarian cancer cell lines.

• Communications for Statistical Applications and Methods
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• v.25 no.6
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• pp.605-618
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• 2018

Risk management has been a crucial part of the daily operations of the financial industry over the past two decades. Value at Risk (VaR), a quantitative measure introduced by JP Morgan in 1995, is the most popular and simplest quantitative measure of risk. VaR has been widely applied to the risk evaluation over all types of financial activities, including portfolio management and asset allocation. This paper uses the implementations of multivariate GARCH models and copula methods to illustrate the performance of a one-day-ahead VaR prediction modeling process for high-dimensional portfolios. Many factors, such as the interaction among included assets, are included in the modeling process. Additionally, empirical data analyses and backtesting results are demonstrated through a rolling analysis, which help capture the instability of parameter estimates. We find that our way of modeling is relatively robust and flexible.