• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.1
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• pp.751-758
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• 2021

Munitions must be analyzed to identify any risks for quality assurance in development and mass production. Risk identification for parts, compositions, and systems is carried out through failure mode effects analysis (FMEA) as one of the most reliable methods. FMEA is a design tool for the failure mode of risk identification and relies on the RPN (risk priority number). FMEA has disadvantages because its severity, occurrence, and detectability are rated at the same level. Fuzzy FMEA applies fuzzy logic to compensate for the shortcomings of FMEA. The fuzzy logic of Fuzzy FMEA is to express uncertainties about the phenomenon and provides quantitative values. In this paper, Fuzzy FMEA is applied to the failure mode of a rotorcraft landing system. The Fuzzy rule and membership functions were conducted in the Fuzzy model to study the RPN in the failure mode of a landing system. This method was selected to demonstrate crisp values of severity, occurrence, and detectability. In addition, the RPN was obtained. The results of Fuzzy FMEA for the landing system were analyzed for the RPN and ranking by fuzzy logic. Finally, Fuzzy FMEA confirmed that it could use the data in quality assurance activities for rotorcraft.

• Journal of Information Technology Services
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• v.19 no.6
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• pp.145-159
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• 2020

Because of the recent development of information and communication technology, companies are exposed to various media such as blogs, social media, and YouTube. In particular, exposed news affects the company's reputation. So, while positive news can improve corporate value, negative news can lead to financial losses for the company. In this study, we redefine corporate reputation as social responsibility, vision and leadership, financial performance, products and services through existing literature, and conducted an AHP survey with a total of four components to calculate the weight of each factor. As a result of the calculation, the proportion of financial performance was the highest at 0.41, and products and services, vision and leadership, and social responsibility were the lowest. In addition, in order to measure the reputation of a company, it is classified as a component that defines online news using the LDA technique. In addition, through sentiment analysis, an index for each corporate reputation factor was derived, and the reputation index was calculated by combining it with the AHP analysis result, and Spearman ranking correlation analysis was performed to secure the validity of the research results. Therefore, the significance of this study is that the definition and importance of the constituent factors can contribute to the future planning and development direction of the company, and also contribute to the derivation of the corporate reputation index. This study is significant in that a new analysis methodology that applied AHP analysis results to sentiment analysis was suggested.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.5
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• pp.55-61
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• 2022

With the rapid development of information technology, Metaverse and Non-Fungible Token (hereinafter referred to as NFT) technology will not only create new supply and demand markets for digital art creators, but also for existing art writers. As interest in and trading of virtual assets and coins increases, so does the demand for digital art trading in the NFT market. This study examines the theoretical content of NFTs, blockchains, and Metaverse, and analyzes various expressions of NFT art that are currently popular. As the case study, 100 projects were selected and analyzed in the overall OpenSea ranking, which included 2D graphics, 3D graphics and motion graphics works. Then, from the perspective of creators, the graphic styles of NFT digital art are divided into 4 types: 2D graphics, 3D graphics, 2D dynamic graphics, 3D dynamic graphics, and analyzed and studied. It is hoped that in the future, this study can suggest the direction of creating graphic styles to digital art NFT creators.

• Rubber Technology
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• v.22 no.2
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• pp.119-149
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• 2021

Domestic materials & components industry is making a shift from quantitative growth to qualitative growth, while the paradigm of a future society is changing rapidly to energy, mobility, smartification and etc. The main features of materials & components industry are analyzed broadly based on three aspects that are: ① industry Status, ② the value chain structure, ③ the competitiveness. With regard to the national aspect, it is shown that the number of an export and a trade surplus increased consistently after the government advanced the policy on materials & components and Korea's trade deficit with Japan has been decreased. Moreover, the state's export ranking increased from tenth place in 2001 into sixth place in 2017, dedicating to the growth of a national economy. The analysis of the chain value indicates that specifications of an end product are set when the materials & components are combined with manpower, infrastructure and technologies. In terms of the competitiveness, it requires a long time and high costs to develop technologies on materials and it is important for components to have a process innovation and credibility wired. Following the industry structure with priority given on materials, Jeonnam Province accounts for 14.8% of national material production. As a result of analyzing Jeonnam's export competitiveness, it is measured that a serious polarization exists, revealing there are 6 major technology industries by 11 categories for materials & components, Jeonnam has presented 6 major materials & components considering the key industry and the new industry in future to remedy the mentioned problem so far, and plans to knock on the industry development through 10 different strategies.

• The Journal of the Convergence on Culture Technology
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• v.7 no.4
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• pp.577-582
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• 2021

This study was conducted to find ways to restore the domestic medical tourism industry, which was seriously hit by a sharp drop in foreign patients after the COVID-19 Pandemic. Kendall's W verification was used by asking expert panel for keyword advice by ranking. The conclusion of the study is that institutions attracting foreign patients need an opportunity to turn the crisis situation into an opportunity by expanding treatment for severe foreign patients. In addition, it is possible to gain familiarity and trust in hospitals in situations where it is difficult to visit overseas through virtual and augmented reality, and to prevent the risk of infection and protect patients in the untact era. In addition, the blockchain can maintain patient information supplementation, share it safely, minimize customer inconvenience by using payment means using virtual currency, and finally, smart healthcare can manage and provide information to patients regardless of location.

• Geomechanics and Engineering
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• v.30 no.6
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• pp.489-502
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• 2022

In this study, a Gaussian process regression (GPR) model as well as six GPR-based metaheuristic optimization models, including GPR-PSO, GPR-GWO, GPR-MVO, GPR-MFO, GPR-SCA, and GPR-SSO, were developed to predict fly-rock distance in the blasting operation of open pit mines. These models included GPR-SCA, GPR-SSO, GPR-MVO, and GPR. In the models that were obtained from the Soungun copper mine in Iran, a total of 300 datasets were used. These datasets included six input parameters and one output parameter (fly-rock). In order to conduct the assessment of the prediction outcomes, many statistical evaluation indices were used. In the end, it was determined that the performance prediction of the ML models to predict the fly-rock from high to low is GPR-PSO, GPR-GWO, GPR-MVO, GPR-MFO, GPR-SCA, GPR-SSO, and GPR with ranking scores of 66, 60, 54, 46, 43, 38, and 30 (for 5-fold method), respectively. These scores correspond in conclusion, the GPR-PSO model generated the most accurate findings, hence it was suggested that this model be used to forecast the fly-rock. In addition, the mutual information test, also known as MIT, was used in order to investigate the influence that each input parameter had on the fly-rock. In the end, it was determined that the stemming (T) parameter was the most effective of all the parameters on the fly-rock.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.136-136
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• 2021

In this study, a deep convolutional neural network (DCNN) model is proposed for short-term precipitation forecasting using weather radar-based images. The DCNN model is a combination of convolutional neural networks, autoencoder neural networks, and U-net architecture. The weather radar-based image data used here are retrieved from competition for rainfall forecasting in Korea (AI Contest for Rainfall Prediction of Hydroelectric Dam Using Public Data), organized by Dacon under the sponsorship of the Korean Water Resources Association in October 2020. This data is collected from rainy events during the rainy season (April - October) from 2010 to 2017. These images have undergone a preprocessing step to convert from weather radar data to grayscale image data before they are exploited for the competition. Accordingly, each of these gray images covers a spatial dimension of 120×120 pixels and has a corresponding temporal resolution of 10 minutes. Here, each pixel corresponds to a grid of size 4km×4km. The DCNN model is designed in this study to provide 10-minute predictive images in advance. Then, precipitation information can be obtained from these forecast images through empirical conversion formulas. Model performance is assessed by comparing the Score index, which is defined based on the ratio of MAE (mean absolute error) to CSI (critical success index) values. The competition results have demonstrated the impressive performance of the DCNN model, where the Score value is 0.530 compared to the best value from the competition of 0.500, ranking 16^th out of 463 participating teams. This study's findings exhibit the potential of applying the DCNN model to short-term rainfall prediction using weather radar-based images. As a result, this model can be applied to other areas with different spatiotemporal resolutions.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.967-974
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• 2022

It is no news that Nigeria's infrastructure challenge is enormous. In the global ranking, Nigeria ranked low in quantity and quality of its infrastructural provision which has a great impact on the ease of business transaction. Low investments in transportation have brought about the current infrastructural deficit. Recently, the Nigerian government has made effort to address at least to some extent the infrastructural deficit through Public-Private Partnership, but this has not yielded the desired result. Moreover, the sustainability issues relating to railway projects such as, emissions, noise pollution, ecosystem, and other environmental issues calls for urgent attention. Hence, this necessitated consideration on sustainability appraisal for the Chinese rail project in Nigeria. This study reviews sustainability of railway projects built by the Chinese firm in Nigeria with particular emphasis on the environmental and social impact of these projects. The study further identified issues and challenges in project implementation with a particular focus on civil dialogue and community engagements. A detailed literature search was conducted on railway projects and infrastructure by systematically reviewing selected published articles.The analysis of the selected articles identified sustainability issues and potential for improvement of Chinese railway projects and how they contribute to or inhibit competitiveness in the Nigerian railway market. From the literature searched, some of the projects constructed by Chinese firm revealed that there is economic and social impact of railway projects delivered by the Chinese firm in terms of capacity development and knowledge transfer potentiality. For instance, in the just concluded Lagos-Ibadan railway projects, the study gathered that the project brought about 5000 jobs and local staff were trained by the Chinese company, this will boost man power and local content capability. Also, it will significantly improve Nigeria's infrastructure and boost its economic development. The study suggests that Nigerian government should ensure and provide an enabling environment that is conducive for investment on the continent. Peace, improved security, and decent governance are the best conditions for sustainable transportation growth.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.59 no.4
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• pp.362-376
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• 2023

The IUU Fishing Index is composed of 40 indicators. These indicators were grouped by state responsibilities (flag, coastal, port, and general including market) defined in the FAO IPOA-IUU (2001) and then by type into vulnerability, prevalence, and response. A total of 152 coastal nations was surveyed. Korea's total combined IUU Fishing Index was 2.49 in 2019 and 2.91 in 2021, indicating a drop in the ranking to the third worst out of 152 countries followed by China and Russia in 2021. The indicators that increased the IUU fishing risk in 2021 compared to 2019 included seven indicators of prevalence and two indicators of response while those reducing the risk included one prevalence and one response indicator. The IUU Fishing Index revealed that many fisheries observers and monitoring, control and surveillance (MCS) practitioners active in the waters of RFMOs jurisdiction where Korean distant water vessels operate have mentioned concerns about the compliance with RFMO conservation measures or fishing practices. It suggested that strengthening management intervention in the fishing sector is needed. The primary tool for management is the MCS system. Given the logistical difficulty of oversight from land, air and at-sea, there is a need to enhance MCS strategies through logbook data, at-sea observer and electronic monitoring program. It also suggested that MSC fisheries certification and fisheries improvement projects, which are widely used for improving fishing sector performance, could contribute to the eradication of IUU fishing and the promotion of sustainable distant water fisheries.

• Journal of Integrative Natural Science
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• v.16 no.3
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• pp.81-95
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• 2023

Colorectal cancer is one of the most common types of cancer worldwide, ranking third after lung and breast cancer in terms of global prevalence. With an expected 1.93 million new cases and 935,000 deaths in 2020, it is more prevalent in males than in women. Evidence has shown that during the later stages of colon cancer, STAT1 promotes tumor progression by promoting cell survival and resistance to chemotherapy. Recent studies have shown that inhibiting STAT1 pathway leads to a reduction in tumor cell proliferation and growth, and can also promote apoptosis in colon cancer cells. One of the recent approaches in the field of drug discovery is drug repurposing. In drug repurposing approach we have virtually screened FDA database against STAT1 protein and their interactions have been studied through Molecular docking. Cross docking was performed with the top 10 compounds to be more specific with STAT1 comparing the affinity with STAT2, STAT3, STAT4, STAT5a, STAT5b and STAT6. The drugs that showed higher affinity were subjected to Conceptual - Density functional theory. Besides, the Molecular dynamic simulation was also carried out for the selected leads. We also validated in-vitro against colon cancer cell lines. The results showed mainly Acetyldigitoxin has shown better binding to the target. From this study, we can predict that the drug Acetyldigitoxin has shown noticeable inhibitory efficiency against STAT1, which in turn can also lead to the reduction of tumor cell growth in colon cancer.