• Journal of the Korean Society of Industry Convergence
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• v.27 no.3
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• pp.609-618
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• 2024

System reliability prediction in the development stage is increasingly crucial to reliability growth management to satisfy its target reliability, since modern system usually takes a form of complex composition and various complicated functions. In most cases of development stage, however, the information available for system reliability prediction is very limited, making it difficult to predict system reliability more precisely as in the production and operating stages. In this study, a system reliability prediction process is considered when the reliability-related information such as SIL (Safety Integrity Level) and MTTFd (Mean Time to Dangerous Failure) is available in the development stage. It is suggested that when the SIL or MTTFd of a system component is known and the field operational data of similar system is given, the reliability prediction could be performed using the scaling factor for the SIL or MTTFd value of the component based on the similar system's field operational data analysis. Predicting a system reliability is then adjusted with the conversion factor reflecting the temperature condition of the environment in which the system actually operates. Finally, the case of applying the proposed system reliability prediction process to a high performance mooring platform is dealt with.

• Analyses & Alternatives
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• v.8 no.2
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• pp.117-140
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• 2024

Major countries are actively pursuing policies to promote entrepreneurship to foster economic growth and employment. Meanwhile, although South Korea's entrepreneurial ecosystem has shown robust quantitative growth since the COVID-19 pandemic, it is still criticized for its shortcomings compared to other major countries. Based on this, this study aims to derive a comprehensive innovation entrepreneurship index for each country to foster an innovative entrepreneurial ecosystem and sustainable growth in South Korea. Specifically, this study first analyzed the entrepreneurial ecosystem of various countries. Second, we utilizing data from sources such as the Global Entrepreneurship Monitor, Global Innovation Index, and World Bank, the study calculates a comprehensive innovation entrepreneurship index for each country. Finally, this study analyzes the type of South Korea's innovation entrepreneurship index and suggests the future direction of through cluster analysis.

• Journal of Microbiology and Biotechnology
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• v.34 no.2
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• pp.270-279
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• 2024

Macrophages are versatile immune cells that play crucial roles in tissue repair, immune defense, and the regulation of immune responses. In the context of skeletal muscle, they are vital for maintaining muscle homeostasis but macrophage-induced chronic inflammation can lead to muscle dysfunction, resulting in skeletal muscle atrophy characterized by reduced muscle mass and impaired insulin regulation and glucose uptake. Although the involvement of macrophage-secreted factors in inflammation-induced muscle atrophy is well-established, the precise intracellular signaling pathways and secretion factors affecting skeletal muscle homeostasis require further investigation. This study aimed to explore the regulation of macrophage-secreted factors and their impact on muscle atrophy and glucose metabolism. By employing RNA sequencing (RNA-seq) and proteome array, we uncovered that factors secreted by lipopolysaccharide (LPS)-stimulated macrophages upregulated markers of muscle atrophy and pro-inflammatory cytokines, while concurrently reducing glucose uptake in muscle cells. The RNA-seq analysis identified alterations in gene expression patterns associated with immune system pathways and nutrient metabolism. The utilization of gene ontology (GO) analysis and proteome array with macrophage-conditioned media revealed the involvement of macrophage-secreted cytokines and chemokines associated with muscle atrophy. These findings offer valuable insights into the regulatory mechanisms of macrophage-secreted factors and their contributions to muscle-related diseases.

• Management & Information Systems Review
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• v.39 no.2
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• pp.39-60
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• 2020

Block chain technology is one of the core elements for realizing the 4^th industrial revolution, and many efforts have been made by government and companies to provide services based on block chain technology. In this study we analyzed the benefits of block chain technology for EVMS and designed EVMS block chain platform with increased data security and work efficiency for project management data, which are important assets in monitoring progress, foreseeing future events, and managing post-completion. We did the case studies on the benefits of block chain technology and then conducted the survey study on security, reliability, and efficiency of block chain technology, targeting 18 block chain experts and project developers. And then, we interviewed EVMS system operator on the compatibility between block chain technology and EVM Systems. The result of the case studies showed that block chain technology can be applied to financial, logistic, medical, and public services to simplify the insurance claim process and to improve reliability by distributing transaction data storage and applying security·encryption features. Also, our research on the characteristics and necessity of block chain technology in EVMS revealed the improvability of security, reliability, and efficiency of management and distribution of EVMS data. Finally, we designed a network model, a block structure, and a consensus algorithm model and combined them to construct a conceptual block chain model for EVM system. This study has the following contribution. First, we reviewed that the block chain technology is suitable for application in the defense sector and proposed a conceptual model. Second, the effect that can be obtained by applying block chain technology to EVMS was derived, and the possibility of improving the existing business process was derived.

• The Korean Journal of Mycology
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• v.29 no.1
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• pp.41-46
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• 2001

Oxidative stress and defense system of SD-rats were studied with an edible Nigerian mushroom, namely, Lentinus tuber-regium (Fries) Singer. Experimental diets prepared with Lentinus tuber-regium (LTR) instead of carbohydrates were fed to SD rats for 6 weeks. Hydrolxyl radical $({\cdot}OH)$ formations were significantly inhibited (21.7% and 16.4%, respectively). In LTR-50 and LTR-100 groups used instead of carbohydrates, and hydrogen peroxide and nitric oxide (NO) were also significantly inhibited by 10%, and $6{\sim}10%$, respectively compared with control group, but there was no significant changes in superoxide radical $({O_2}^-)$ formations in these groups. Lipid peroxide (LPO) and oxidized protein (OP) levels as an oxidative stress were desirably inhibited ($6{\sim}12%\;and\;5{\sim}13%$, respectively) in these LTR groups compared with control group. Superoxide dismutase (SOD), glutathione peroxidase (GSHPx) and catalase (CAT) activities were significantly increased ($15{\sim}50%,\;10{\sim}25%\;and\;60{\sim}90%$, respectively) in these LTR groups. These results suggest that an edible mushroom, Lentinus tuber-regium may inhibit an oxygen radicals and oxidative stresses, but may also effectively modulate an aging processes.

• Korean Journal of Optics and Photonics
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• v.33 no.4
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• pp.167-176
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• 2022

Adaptive optics (AO) systems compensate for atmospheric disturbance, especially phase distortion, by introducing counter-wavefront deformation calculated from real-time wavefront sensing or prediction. Because AO system implementations are time-consuming and costly, it is highly desirable to estimate the system's performance during the development of the AO system or its parts. Among several techniques, we mostly apply statistical analysis, computational simulation, and optical-bench tests. Statistical analysis estimates performance based on the sum of performance variances due to all design parameters, but ignores any correlation between them. Computational simulation models every part of an adaptive optics system, including atmospheric disturbance and a closed loop between wavefront sensor and deformable mirror, as close as possible to reality, but there are still some differences between simulation models and reality. The optical-bench test implements an almost identical AO system on an optical bench, to confirm the predictions of the previous methods. We are currently developing an AO system for a 1.6-m ground telescope using a deformable mirror that was recently developed in South Korea. This paper reports the results of the statistical analysis and computer simulation for the system's design and confirmation. For the analysis, we apply the Strehl ratio as the performance criterion, and the median seeing conditions at the Bohyun observatory in Korea. The statistical analysis predicts a Strehl ratio of 0.31. The simulation method similarly reports a slightly larger value of 0.32. During the study, the simulation method exhibits run-to-run variation due to the random nature of atmospheric disturbance, which converges when the simulation time is longer than 0.9 seconds, i.e., approximately 240 times the critical time constant of the applied atmospheric disturbance.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.5
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• pp.1128-1134
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• 2014

Web based simulation service is actively utilized to computably analyze various kinds of phenomena in real world according to progress of computing technology and spread of Network. However it is hard to share data and information among users on the services, because most of web based simulation services do not share and open simulation processing information and results. In this paper, we design a simulation provenance data sharing service on EDISON_CFD (EDucation-research Integration Simulation On the Net for Computational Fluid Dynamics) to share the calculated simulation performance information. To store and share the simulation processing information, we define the simulation processing step as "Problem ${\rightarrow}$ Plan, Design ${\rightarrow}$ Mesh ${\rightarrow}$ Simulation performance ${\rightarrow}$ Result ${\rightarrow}$ Report." Users can understand a problem solving method through a computer simulation by searching the simulation performance information with Search/Share API of the store. Besides, this opened simulation information can reduce the waste of calculation resource to process same simulation jobs.

• Korean Journal of Environmental Biology
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• v.29 no.3
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• pp.236-240
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• 2011

Mercury known as quicksilver, is the most common cause of heavy metal toxicity. Toxicity caused by excessive mercury exposure is now being recognized as a widespread environmental problem and is continuing to attract a great deal of public concerns. The mercury genotoxicity could be its effect on DNA repair mechanisms, which constitute the defense system designated to protect genome integrity. The objective of this study is to confirm that mercuric chloride inhibits the repair of gamma ray-induced DNA damage. The earthworm of Eisenia fetida was chosen for this study because it is an internationally accepted model species for toxicity testing with a cosmopolitan distribution. Experiments were done to identify the levels of DNA damage and the repair kinetics in the coelomocytes of E. fetida irradiated with 20 Gy gamma rays alone or with gamma rays after 40 mg $kg^{-1}$ $HgCl_2$ treatment by means of the single cell gel electrophoresis assay. The Olive tail moments were measured during 0~96 hours after irradiation. The repair time in the animals treated with the combination of $HgCl_2$ and ionizing radiation was nearly five times longer than that in the animals treated with ionizing radiation alone. Also, E. fetida exposed to mercury showed a statistically lower repair efficiency of gamma ray-induced DNA damage. The results suggest that the mercury could even have deleterious effects on the DNA repair system. Influence of mercury on the DNA repair mechanisms has been confirmed by this study.

• Journal of the Korea Society of Computer and Information
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• v.25 no.9
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• pp.37-44
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• 2020

AI technology has developed in the form of decision support technology in law, patent, finance and national defense and is applied to disease diagnosis and legal judgment. To search real-time information with Deep Learning, Big data Analysis and Deep Learning Algorithm are required. In this paper, we try to predict the entrance rate to high-ranking universities using a Deep Learning model, RNN(Recurrent Neural Network). First, we analyzed the current status of private academies in administrative districts and the number of students by age in administrative districts, and established a socially accepted hypothesis that students residing in areas with a high educational fever have a high rate of enrollment in high-ranking universities. This is to verify based on the data analyzed using the predicted hypothesis and the government's public data. The predictive model uses data from 2015 to 2017 to learn to predict the top enrollment rate, and the trained model predicts the top enrollment rate in 2018. A prediction experiment was performed using RNN, a Deep Learning model, for the high-ranking enrollment rate in the special education zone. In this paper, we define the correlation between the high-ranking enrollment rate by analyzing the household income and the participation rate of private education about the current status of private institutes in regions with high education fever and the effect on the number of students by age.

• Clean Technology
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• v.22 no.3
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• pp.190-195
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• 2016

The thermal decomposition of waste energetic materials such as TNT, RDX and composition B in a commercial rotary kiln has previously been carried out. As part of the demilitarization process, the thermal decomposition of homogeneous double base propellant (DB) used in M8 and consisting predominantly of nitrocellulose and nitroglycerine is examined with respect to a number of operating conditions. A single condensed phase reaction with 4 species and 365 gas phase reactions and 59 species are considered. Simulation results show the sensitivity of the thermal decomposition of DB with temperature and velocity. At relatively low velocity with constant inlet hot air temperature, temperature in the rotary kiln was found to be highest, 953 K and 1300 K for cases 3 and 6 respectively. Illustrating that optimum operating temperature can be achieved by controlling the inlet velocity without additional cooling systems.