• Mycobiology
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• v.49 no.3
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• pp.235-248
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• 2021

This study aimed to understand whether the geo-ecological segregation of native plant species affects the root-associated fungal community. Rhizoplane (RP) and rhizosphere (RS) fungal microbiota of Sedum takesimense native to three geographically segregated coastal regions (volcanic ocean islands) were analyzed using culture-independent methods: 568,507 quality sequences, 1399 operational taxonomic units, five phyla, and 181 genera were obtained. Across all regions, significant differences in the phyla distribution and ratio were confirmed. The Chao's richness value was greater for RS than for RP, and this variance coincided with the number of genera. In contrast, the dominance of specific genera in the RS (Simpson value) was lower than the RP at all sites. The taxonomic identity of most fungal species (95%) closely interacting with the common host plant was different. Meanwhile, a considerable number of RP only residing fungal genera were thought to have close interdependency on their host halophyte. Among these, Metarhizium was the sole genus common to all sites. These suggest that the relationship between potential symbiotic fungi and their host halophyte species evolved with a regional dependency, in the same halophyte species, and of the same natural habitat (volcanic islands); further, the fungal community differenced in distinct geographical regions. Importantly, geographical segregation should be accounted for in national culture collections, based on taxonomical uniqueness.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.4
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• pp.81-90
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• 2018

Modern investment theory has empirically proved that stock returns can be explained by several factors such as market risk, firm size, and book-to-market ratio. Other unknown factors affecting stock returns are also believed to still exist yet to be found. We believe that one of such factors is the operational efficiency of firms in transforming inputs to outputs, considering the fact that operations is a fundamental and primary function of any type of businesses. To support this belief, this study intends to empirically study the relationship between firm efficiency and stock price performance. Firm efficiency is measured using data envelopment analysis (DEA) with inputs and outputs obtained from financial statements. We employ cross-efficiency evaluation to enhance the discrimination power of DEA with a secondary objective function of aggressive formulation. Using the CAPM-based performance regression model, we test the performance of equally weighted portfolios of different sizes selected based upon DEA cross-efficiency scores along with a buy & hold trading strategy. For the empirical test, we collect financial data of domestic firms listed in KOSPI over the period of 2000~2016 from well-known financial databases. As a result, we find that the porfolios with highly efficient firms included outperform the benchmark market portfolio after controlling for the market risk, which indicates that firm efficiency plays a important role in explaining stock returns.

• Journal of the Korea Institute of Military Science and Technology
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• v.21 no.6
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• pp.886-893
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• 2018

U.S. and the allies attacked chemical weapons sites in Syria in 2018, and verbal battles are carried out about the effectiveness of the air strike. Syria claimed 13 missiles were shot down, and Russia claimed 71 missiles were shot down while the U.S. released pictures of completely destroyed targets, only. It led controversy about the effectiveness of missile defense system. If there is a method to observe mission success rate of the air strike, it can not only improve combat awareness but also can be a good sales strategy in military industry. This paper describes effects and considerations of a Weapon Data Link(WDL) technology which can be used as a smoking gun of effectiveness. The paper describes WDL abilities such as In-Flight Track Update, Loiter, and Bomb Hit Indication etc., and presents examples of expected effectiveness of the WDL. In addition, this paper briefly summarizes operational consideration for better performance.

• Journal of the Korea Institute of Military Science and Technology
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• v.21 no.6
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• pp.877-885
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• 2018

The anti-submarine helicopter is the most effective weapon system in anti-submarine warfare. Recently changes in the introduction of the anti-submarine warfare sonar system are expected to operate multi-static sonar equipment of the anti-submarine helicopter. Therefore, it is required to study the operational concept of multi-static of anti-submarine helicopter. This paper studies on the optimal search of multi-static based on anti-submarine helicopter considering Furthest On Circles(FOC). First, the deployment of the sensors of the anti-submarine helicopter is optimized using genetic algorithms. Then, the optimized model is extended to consider FOC. Finally, the proposed model is verified by comparing pattern-deployment the search method in Korean Navy.

• Safety and Health at Work
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• v.12 no.1
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• pp.1-9
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• 2021

This review article addresses the role of safety professionals in the diffusion strategies for predictive analytics for safety performance. The article explores the models, definitions, roles, and relationships of safety professionals in knowledge application, access, management, and leadership in safety analytics. The article addresses challenges safety professionals face when integrating safety analytics in organizational settings in four operations areas: application, technology, management, and strategy. A review of existing conventional safety data sources (safety data, internal data, external data, and context data) is briefly summarized as a baseline. For each of these data sources, the article points out how emerging analytic data sources (such as Industry 4.0 and the Internet of Things) broaden and challenge the scope of work and operational roles throughout an organization. In doing so, the article defines four perspectives on the integration of predictive analytics into organizational safety practice: the programmatic perspective, the technological perspective, the sociocultural perspective, and knowledge-organization perspective. The article posits a four-level, organizational knowledge-skills-abilities matrix for analytics integration, indicating key organizational capacities needed for each area. The work shows the benefits of organizational alignment, clear stakeholder categorization, and the ability to predict future safety performance.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.3
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• pp.447-456
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• 2021

Methods for predicting the ultimate/buckling strength of ship structures have been extensively improved in terms of design formulas and analytical solutions. In recent years, the design strategy of ships and offshore structures has tended to emphasize lighter builds and improve operational safety. Therefore, the corresponding geometrical changes in design necessitate the use of high-tensile steel and thin plates. However, the existing design formulas were mainly developed for thick plates and mild steels. Therefore, the calculation methods require appropriate modification for new designs beased on high-tensile steel and thin plates. In this study, a modified formula was developed to predict the ultimate strength of thin steel plates subjected to compressive and shear loads. Based on the numerical results, the effects of the yield stress, slenderness ratio, and loading condition on the buckling/ultimate strength of steel plates were examined, and a newly modified double-beta parameter formula was developed. The results were used to derive and modify existing closed-form expressions and empirical formulas to predict the ultimate strength of thin-walled steel structures.

• Nuclear Engineering and Technology
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• v.52 no.12
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• pp.2928-2938
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• 2020

A light water nuclear Reactor has been exergy analyzed, and the rate of irreversible exergy loss and exergy destruction is calculated for each of its components. The ratio of these losses compared to the total input exergy loss is calculated, which shows that most irreversible losses occur in the reactors, turbines, steam generators, respectively, as well as in the downstream operations. The main aim of this paper is to optimize the power plant using an innovative firefly algorithm and then to propose a novel strategy to improve the overall performance of the plant. As shown in the results, the exergy destruction rate of the plant decreased by 1.18% using the firefly method, and the exergy efficiency of the plant reached 29.3% comparing to the operational amount of 28.99%. Also, the results of the firefly optimization process compared to the Genetic algorithm and gravitational search algorithm to study the accuracy of the model for exergy analysis fitness problems in the power plants and the results of this comparison has shown that the results are nearly similar in the mentioned methods. However, the firefly is faster and more accurate in limited iterations.

• Journal of the Society of Naval Architects of Korea
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• v.59 no.6
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• pp.372-384
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• 2022

Total shipping accounts for 2.9 % of the annual average percentage of global anthropogenic GHG emissions. The International Maritime Organization implements EEDI (Energy Efficiency Design Index), Energy Efficiency eXisting-ship Index (EEXI), and Carbon Intensity Indicator (CII) as regulatory frameworks for shipping decarbonization. The Republic of Korea has enforced the Act on Development and Popularization of Greenship from 2020 and publicly announced the 1st national plan which was named 『2030 Greenship-K Promotion Strategy』 for the activation of a greenship market. The Greenship Certification Scheme is going on for the sustainability of Korean shipbuilding and shipping industries, to secure clean maritime environments, as well as to contribute to the national economy. Greenship Certification guarantees the credit of such eco-friendly technologies and products for shipping. The certification is going to be the basis of industrial competitiveness in coastal and international shipping. This study investigates an existing certification process, identifies the limitations, and proposes the process improved with several case studies. The improved certification scheme may have rationality for Net-zero with regard to climate alignment.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.7
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• pp.53-62
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• 2022

Commercial banks have a significant impact on the economy of Vietnam because they provide the majority of transactional capital. Therefore, the operational efficiency of commercial banks is a viral topic for the study of the Vietnamese banking system. The research aims to examine the efficiency and inefficiency of joint-stock commercial banks in Vietnam from 2016 to 2020 and then classify them into the efficient group and inefficient group. The study employs the time series data of 29 joint-stock commercial banks during the period 2016-2020. Based on the data collected from the annual audited financial statements of 29 Vietnamese joint-stock commercial banks, the authors select input and output variables for the standard DEA models and anti-efficient DEA models. This research uses two stages, first, by applying the standard DEA model, we investigate the efficient banks; second, by employing the anti-efficient DEA model, we find out the inefficient banks. The results reveal that the average efficiency score of 29 joint-stock commercial banks tends to increase in the period 2016-2018 and decrease gradually in the period 2019-2020. The findings of this study suggest that several small and medium-sized banks in the Vietnamese banking sector have both promising and risky performances and the efficiency of state-owned commercial banks has also improved significantly during the study period.

• Journal of Information Processing Systems
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• v.18 no.5
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• pp.637-649
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• 2022

Investors aim to increase their profitability by investing in the stock market. An adroit strategy for minimizing related risk lies through diversifying portfolio operationalization. In this paper, we propose a six-step stocks portfolio selection model. This model is based on data mining clustering techniques that reflect the ensuing impact of the political, economic, legal, and corporate governance in Mongolia. As a dataset, we have selected stock exchange trading price, financial statements, and operational reports of top-20 highly capitalized stocks that were traded at the Mongolian Stock Exchange from 2013 to 2017. In order to cluster the stock returns and risks, we have used k-means clustering techniques. We have combined both k-means clustering with Markowitz's portfolio theory to create an optimal and efficient portfolio. We constructed an efficient frontier, creating 15 portfolios, and computed the weight of stocks in each portfolio. From these portfolio options, the investor is given a choice to choose any one option.