• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.11
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• pp.2033-2038
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• 2016

Big data analysis, in the large amount of data stored as the data warehouse which it refers the process of discovering meaningful new correlations, patterns, trends and creating new values. The important issue of a meta-analysis is not the significance test, the effect size of the predictor variable on the criterion variable. We reviewed a total of 236 samples among 6 studies published on the topic related Collagen intake on skin between 2000 and 2016 in Korea. The results of the study are summarized as follows. First, we concluded that the path between before and after of Sebum (SB) had the largest effect size of (r = .416) Therefore, the effect of the Collagen intake intervention showed an explanatory power of 17 (%) about. Next, the path between before and after of Moisture (MS) had the higher the effect size of (r = .318). Thus, we present the theoretical and practical implications of these results.

• Journal of Intelligence and Information Systems
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• v.28 no.3
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• pp.23-43
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• 2022

In order to apply AI (Artificial Intelligence) in various industries, interest in algorithm selection is increasing. Algorithm selection is largely determined by the experience of a data scientist. However, in the case of an inexperienced data scientist, an algorithm is selected through meta-learning based on dataset characteristics. However, since the selection process is a black box, it was not possible to know on what basis the existing algorithm recommendation was derived. Accordingly, this study uses k-means cluster analysis to classify types according to data set characteristics, and to explore suitable classification algorithms and methods for resolving class imbalance. As a result of this study, four types were derived, and an appropriate class imbalance resolution method and classification algorithm were recommended according to the data set type.

• Journal of Smart Tourism
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• v.2 no.1
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• pp.21-31
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• 2022

This review paper aims at providing a systematic analysis of articles published in various journals and related to the uses and business applications of big data. The goal is to provide a holistic picture of the place of big data in the tourism industry. The reviewed articles have been selected for the period 2013-2020 and have been classified into 8 broad categories namely business strategy and firm performance; banking and finance; healthcare; hospitality; networks and telecommunications; urbanism and infrastructures; law and legal regulations; and government. While the categories are reflective of components of tourism industries and infrastructures, the meta-analysis is organized around 3 broad themes: preferred research contexts, conceptual developments, and methods used to research big data business applications. Main findings revealed that firm performance and healthcare remain popular contexts of research in the big data realm, but also demonstrated a prominence of qualitative methods over mixed and quantitative methods for the period 2013-2020. Scholars have also investigated topics involving the notions of competitive advantage, supply chain management, smart cities, but also ethics and privacy issues as related to the use of big data.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.646-649
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• 2022

Media is a means for exchanging one's emotions or objective information in human society. Due to the spread of smart media due to the advent of digital media, media in modern society is not a simple means but encompasses the entire society in which humans live. It even took over the control function. Therefore, by examining the types and characteristics of media according to the service platform in which smart media is used, and building a big data hub for media based on this, new development and research directions for digital media can be explored. In this paper, we analyze various metadata generated through smart media and propose a plan for building a big data platform using it.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.6
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• pp.3719-3724
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• 2013

Background: RASSF1A has been reported to be a candidate tumor suppressor in non-small cell lung cancer (NSCLC). However, the association between RASSF1A promoter methylation and NSCLC remains unclear, particularly in regarding links to clinicopathologic features. Methods: Eligible studies were identified through searching PubMed, EMBASE, Cochrane Library and China National Knowledge Infrastructure (CNKI) databases. Studies were pooled and odds ratios (ORs) with corresponding confidence intervals (CIs) were calculated. Funnel plots were also performed to evaluate publication bias. Results: Nineteen studies involving 2,063 cases of NSCLC and 1,184 controls were included in this meta-analysis. A significant association was observed between RASSF1A methylation and NSCLC in the complete data set (OR = 19.42, 95% CI: 14.04-26.85, P < 0.001). Pooling the control tissue subgroups (heterogeneous/autologous) gave pooled ORs of 32.4 (95% CI, 12.4-84.5) and 17.7 (95% CI, 12.5-25.0) respectively. Racial subgroup (Caucasian/Asian) analysis gave pooled ORs of 26.6 (95% CI, 10.9-64.9) and 20.9 (95% CI, 14.4-30.4) respectively. The OR for RASSF1A methylation in poorly-differentiated vs. moderately/well-differentiated NSCLC tissues was 1.88 (95% CI, 1.32-2.68, P<0.001), whereas there were no significant differences in RASSF1A methylation in relation to gender, pathology, TNM stage and smoking behavior among NSCLC cases. Conclusion: This meta-analysis suggests a significant association between RASSF1A methylation and NSCLC, confirming the role of RASSF1A as a tumor suppressor gene. Large-scale and well-designed case-control studies are needed to validate the associations identified in the present meta-analysis.

• Biotechnology and Bioprocess Engineering:BBE
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• v.10 no.5
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• pp.425-431
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• 2005

The systems-level analysis of microbes with myriad of heterologous data generated by omics technologies has been applied to improve our understanding of cellular function and physiology and consequently to enhance production of various bioproducts. At the heart of this revolution resides in silico genome-scale metabolic model, In order to fully exploit the power of genome-scale model, a systematic approach employing user-friendly software is required. Metabolic flux analysis of genome-scale metabolic network is becoming widely employed to quantify the flux distribution and validate model-driven hypotheses. Here we describe the development of an upgraded MetaFluxNet which allows (1) construction of metabolic models connected to metabolic databases, (2) calculation of fluxes by metabolic flux analysis, (3) comparative flux analysis with flux-profile visualization, (4) the use of metabolic flux analysis markup language to enable models to be exchanged efficiently, and (5) the exporting of data from constraints-based flux analysis into various formats. MetaFluxNet also allows cellular physiology to be predicted and strategies for strain improvement to be developed from genome-based information on flux distributions. This integrated software environment promises to enhance our understanding on metabolic network at a whole organism level and to establish novel strategies for improving the properties of organisms for various biotechnological applications.

• Journal of Korea Spatial Information System Society
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• v.6 no.2 s.12
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• pp.39-49
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• 2004

An increasing number of distributed applications will be achieved with mobile technology. These applications face temporary loss of network connectivity when they move. They need to discover other hosts in an ad-hoc manner, and they are likely to have scarce resources including CPU speed, memory and battery power. Software engineers building mobile applications need to use a suitable middleware that resolves these problems and offers appropriate support for developing mobile applications. In this paper, we describe the meta-server building for middleware that addresses reflective context awareness and present usability with demonstration. Metadata is consist of user configuration, device configuration, user context, device context and dynamic image metadata. When middleware send a saving or retrieval request to meta-server, it returns messages to middleware after the verification of the request. This meta-server has the application for multimedia stream services with context awareness.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.12
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• pp.7613-7619
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• 2013

Background and Aims: Helicobacter pylori infection may be associated with an increased risk of colorectal carcinoma. However, as most studies on this subject were relatively small in size and differed at least partially in their designs, their results remain controversial. In this study, we aimed to carry out a meta-analysis to evaluate the potential association of H. pylori infection with colorectal adenoma and adenocarcinoma risk, covering all of the different testing methods. Methods: We conducted a search in PubMed, Medline, EBSCO, High Wire Press, OVID, and EMBASE covering all published papers up to March 2013. According to the established inclusion criteria, essential data were then extracted from the included studies and further analyzed by a systematic meta-analysis. Odds ratios were employed to evaluate the relationship between H. pylori infection and the risk of colorectal neoplasms. Results: Twenty-two studies were included, and the odds ratio for the association between H. pylori infection and colorectal cancer was 1.49 (95% confidence interval 1.30-1.72). No statistically significant heterogeneity was observed. Publication bias was ruled out. Conclusion: The pooled data suggest H. pylori infection indeed increases the risk of colorectal adenoma and adenocarcinoma.

• The Journal of Information Systems
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• v.28 no.4
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• pp.293-311
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• 2019

Purpose This paper is to make a meta-analysis of the relationship between the social media use and learning performance as well as its potential moderating variables to clarify the differences in research conclusions in existing literatures, and refine the situational and method factors that affect the relationship between them. Methodology Meta-analysis used in this study can combine the quantitative data from different empirical studies, focus on the same research problem, and finally reach a research conclusion. Findings The results show that social media use and learning performance have a moderating positive correlation. The moderating effect test of usage scenarios shows that social media types, usage groups, application platforms and discipline fields have moderating effects on the relationship between social media use and learning performance. The moderating effect test of the research method found that measurement models, data attributes and learning performance indicators also had moderating effects on the relationship between social media use and learning performance.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.3
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• pp.1691-1695
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• 2013

Objective: To evaluate the association between tea consumption and the risk of renal cell carcinoma. Methods: We searched PubMed, Web of Science and Scopus between 1970 and November 2012. Two evaluators independently reviewed and selected articles based on predetermined selection criteria. Results: Twelve epidemiological studies (ten case-control studies and two cohort studies) were included in the final analysis. In a meta-analysis of all included studies, when compared with the lowest level of tea consumption, the overall relative risk (RR) of renal cell carcinoma for the highest level of tea consumption was 1.03 (95% confidence interval [CI] 0.89-1.21). In subgroup meta-analyses by study design, there was no significant association between tea consumption and renal cell carcinoma risk in ten case-control studies using adjusted data (RR=1.08, 95% CI 0.84-1.40). Furthermore, there was no significant association in two cohort studies using adjusted data (RR=0.95, 95% CI 0.81-1.12). Conclusion: Our findings do not support the conclusion that tea consumption is related to decreased risk of renal cell carcinoma. Further prospective cohort studies are required.