• The Journal of Asian Finance, Economics and Business
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• v.8 no.8
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• pp.287-296
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• 2021

Stepping into the technological boom time, Vietnam has integrated into the trends of using Fintech applications as a new means of payment. This article evaluates the relationship between perceived security (including service security and platform security), knowledge, confirmation, perceived usefulness, satisfaction, attitude and lastly enterprise's images regarding the service and continuous intention to use Fintech services. The survey results of 352 Vietnamese customers using Fintech services, reliability test and extended post-acceptance model (EPAM) which is based on PAM and ECT models. From the survey, we further found out that perceived security (BSS) has no direct impact on continued intention to use, while perceived security (BSS) has positive impact on confirmation (CON), similarly, perceived usefulness (PU) and user's satisfaction (SES). Knowledge of the Mobile Fintech payment service (KNOW) has a positive impact on perceived security (BSS). Confirmation (CON) has a positive influence on perceived usefulness but in the meanwhile it has created a negative impact on user's satisfaction (SES). From the survey it can also tell that user's attitude (ATT) and enterprise image (IMG) both have a positive impact on continual intention to use Fintech services. From the research results, we also propose some recommendation to enhance the continual intention to use Fintech services in Vietnam.

• Genomics & Informatics
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• v.19 no.3
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• pp.23.1-23.7
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• 2021

Currently, coronavirus disease 2019 (COVID-19) literature has been increasing dramatically, and the increased text amount make it possible to perform large scale text mining and knowledge discovery. Therefore, curation of these texts becomes a crucial issue for Bio-medical Natural Language Processing (BioNLP) community, so as to retrieve the important information about the mechanism of COVID-19. PubAnnotation is an aligned annotation system which provides an efficient platform for biological curators to upload their annotations or merge other external annotations. Inspired by the integration among multiple useful COVID-19 annotations, we merged three annotations resources to LitCovid data set, and constructed a cross-annotated corpus, LitCovid-AGAC. This corpus consists of 12 labels including Mutation, Species, Gene, Disease from PubTator, GO, CHEBI from OGER, Var, MPA, CPA, NegReg, PosReg, Reg from AGAC, upon 50,018 COVID-19 abstracts in LitCovid. Contain sufficient abundant information being possible to unveil the hidden knowledge in the pathological mechanism of COVID-19.

• Journal of Bio-Environment Control
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• v.27 no.1
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• pp.27-33
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• 2018

This study was performed to review the domestic and international smart farm service model based on the convergence of agriculture and information & communication technology and derived various factors needed to improve the Korean smart greenhouse. Studies on modelling of crop growth environment in domestic smart farms were limited. And it took a lot of time to build research infrastructure. The cloud-based research platform as an alternative is needed. This platform can provide an infrastructure for comprehensive data storage and analysis as it manages the growth model of cloud-based integrated data, growth environment model, actuators control model, and farm management as well as knowledge-based expert systems and farm dashboard. Therefore, the cloud-based research platform can be applied as to quantify the relationships among various factors, such as the growth environment of crops, productivity, and actuators control. In addition, it will enable researchers to analyze quantitatively the growth environment model of crops, plants, and growth by utilizing big data, machine learning, and artificial intelligences.

• Journal of Convergence for Information Technology
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• v.10 no.6
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• pp.35-40
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• 2020

As we enter the society of the future, efforts to increase healthy living are a major area of concern for modern people. In particular, the development of technology for a healthy life that combines ICT technology with a competitive healthcare industry environment is becoming the next growth engine. Therefore, in this paper, artificial intelligence-based data analysis of the examination results was applied in the health examination process. Through this, a research was conducted to build a knowledge base modeling that can improve the reliability of the overall judgment. To this end, an algorithm was designed through deep learning analysis to calculate and verify the test result index. Then, the modeling that provides comprehensive examination information through judgment knowledge was studied. Through the application of the proposed modeling, it is possible to analyze and utilize big data on national health, so it can be expected to reduce medical expenses and increase health.

• Korean Journal of Computational Design and Engineering
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• v.17 no.2
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• pp.123-131
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• 2012

The requirements for computational resources to perform the structural analysis are increasing rapidly. The size of the current analysis problems that are required from practical industry is typically large-scale with more than millions degrees of freedom (DOFs). These large-scale analysis problems result in the requirements of high-performance analysis codes as well as hardware systems such as supercomputer systems or cluster systems. In this paper, the pre- and post-processing system for supercomputing based large-scale structural analysis is presented. The proposed system has 3-tier architecture and three main components; geometry viewer, pre-/post-processor and supercomputing manager. To analyze large-scale problems, the ADVENTURE solid solver was adopted as a general-purpose finite element solver and the supercomputer named 'tachyon' was adopted as a parallel computational platform. The problem solving performance and scalability of this structural analysis system is demonstrated by illustrative examples with different sizes of degrees of freedom.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.5
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• pp.385-389
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• 2009

As a new community forming environment, the blog platform enables sharing of the resources in blogosphere through active information exchange. Many researches have been performed to recommend appropriate resources to users from vast amounts of blog resources. As one of the solutions OSEM defines the knowledge base in the blogosphere with ontology for effectively modeling it. In this paper, we propose a technique of converting the knowledge base into the OWL ontology for sharing it on the semantic web environment. An inference method is then applied to the OWL ontology for recommending interest blog communities. For this aim, a mapping method is offered and then SWRL inference and SPARQL query based on the ontology are employed to extract interest blog communities.

• Journal of Computing Science and Engineering
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• v.8 no.4
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• pp.181-186
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• 2014

Web data mining aims at discovering useful knowledge from various Web resources. There is a growing trend among companies, organizations, and individuals alike of gathering information through Web data mining to utilize that information in their best interest. In science, cloud computing is a synonym for distributed computing over a network; cloud computing relies on the sharing of resources to achieve coherence and economies of scale, similar to a utility over a network, and means the ability to run a program or application on many connected computers at the same time. In this paper, we propose a new system framework based on the Hadoop platform to realize the collection of useful information of Web resources. The system framework is based on the Map/Reduce programming model of cloud computing. We propose a new data mining algorithm to be used in this system framework. Finally, we prove the feasibility of this approach by simulation experiment.

• Journal of Nutrition and Health
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• v.55 no.6
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• pp.601-616
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• 2022

In the era of the fourth industrial revolution technology, the inclusion of personalized nutrition for healthcare (PNH), when establishing a healthcare platform to prevent chronic diseases such as obesity, diabetes, cerebrovascular and cardiovascular disease, pulmonary disease, and inflammatory diseases, enhances the national competitiveness of global healthcare markets. Furthermore, since the government experienced COVID-19 and the population dead cross in 2020, as well as numerous health problems due to an increasing super-aged Korean society, there is an urgent need to secure, develop, and utilize PNH-related technologies. Three conditions are essential for the development of PNH technologies. These include the establishment of causality between obesity genome (genotype) and prevalence (phenotype) in Koreans, validation of clinical intervention research, and securing PNH-utilization technology (i.e., algorithm development, artificial intelligence-based platform, direct-to-customer [DTC]-based PNH, etc.). Therefore, a national control tower is required to establish appropriate PNH infrastructure (basic and clinical research, cultivation of PNH-related experts, etc.). The post-corona era will be aggressive in sharing data knowledge and developing related technologies, and Korea needs to actively participate in the large-scale global healthcare markets. This review provides the importance of scientific evidence based on a huge dataset, which is the primary prerequisite for the DTC obesity gene-based PNH technologies to be competitive in the healthcare market. Furthermore, based on comparing domestic and internationally approved DTC obese genes and the current status of Korean obesity genome-based PNH research, we intend to provide a direction to PNH planners (individuals and industries) for establishing scientific PNH guidelines for the prevention of obesity.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.5
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• pp.24-32
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• 2011

According to accelerate the convergence of defense and information technology, there is a need for innovative change in Military e-Learning service system. In other words, It has increased the need for system integration based on standards and interoperability to develop into a network-centric information and knowledge. In this study, It would like to introduce an integrated direction Military e-Learning service system on the SOA-based video content services in the operating system for the operating model. SOA is taking advantage in integration and expansion of the unit with a process. Using it, define of video services platform architecture and define of business model based on the Imprimatur model. Based on this, it define the role of actors for video content service in each step of the operating model, that is Production model, Brokerage model and consumption model. In the operating system, it define the functions and data to control and handle the needed functionality for video content services based on the operational model.

• Journal of Korean Neurosurgical Society
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• v.63 no.5
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• pp.550-558
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• 2020

To perform a systematic review of the data collected from case-control studies conducted earlier to investigate the correlation between E-selectin S128R polymorphism and ischemic stroke (IS) risk among the Chinese population. The PubMed, Web of Science, Chinese biomedical literature database (CBM), Chinese databases China National Knowledge Infrastructure (CNKI), WanfangData knowledge service platform (Wanfang Data), and information resource integration service platform (VIP) Databases were searched to retrieve case-control studies on the correlation between E-selectin gene S128R polymorphism and IS from the inception of the database till June 2019. The literature was screened, data were extracted, the risk of bias was reviewed, and the studies included were assessed independently by two reviewers. Stata ver. 12.0 software (Stata Corp LLC, College Station, TX, USA) was used to perform the meta-analysis. A total of 2907 cases from eight case-control studies involving 1478 IS patients and 1429 controls were included in this study. The R allele and RS genotype in E-selectin were found to be associated with the risk of IS as per the results of the meta-analysis (R vs. S : odds ratio [OR], 2.75; 95% confidence interval [CI], 2.15-3.51; p<0.00001; RS vs. SS : OR, 2.50; 95% CI, 1.95-3.19; p<0.00001; RR+RS vs. SS : OR, 2.85, 95% CI, 2.21-3.67; p<0.00001). The E-selectin gene S128R polymorphism is likely related to IS based on the results of a meta-analysis in the Chinese population, and the R allele and RS genotype of E-selectin may be IS risk factors.