• Korean Journal of Ecology and Environment
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• v.55 no.4
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• pp.390-397
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• 2022

Conservation of Arctic Flora and Fauna (CAFF) is the biodiversity working group of the Arctic Council. CAFF conducts Monitoring, Assessment, Policy, and expert group activities to preserve Arctic biodiversity and ensure the sustainability of biological resources and communicates the results to governments and indigenous peoples. The main tasks of CAFF consist of monitoring (Circumpolar Biodiversity Monitoring Program), assessment (Arctic Biodiversity Assessment) and strategic projects(Arctic Migratory Bird Initiative, AMBI). Korea has been directly participating in the AMBI since 2015 after acquiring observer status of the Arctic Council in 2013. The AMBI aims to preserve habitats on migration routes used by breeding birds in the Arctic and prevent illegal hunting. Thus, observer countries on migratory routes are directly participating in the project. When selecting priorities for participation in Arctic cooperation projects by 2030, Korea should consider continuing participation in AMBI and participating in the "CAFF Youth Program" in connection with the Arctic Academy program operated by Korea's public institutes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.10
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• pp.3989-4006
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• 2020

The intelligent agriculture monitoring is based on the perception and analysis of environmental data, which enables the monitoring of the production environment and the control of environmental regulation equipment. As the scale of the application continues to expand, a large amount of data will be generated from the perception layer and uploaded to the cloud service, which will bring challenges of insufficient bandwidth and processing capacity. A fog-based offline and real-time hybrid data analysis architecture was proposed in this paper, which combines offline and real-time analysis to enable real-time data processing on resource-constrained IoT devices. Furthermore, we propose a data process-ing algorithm based on the incremental principal component analysis, which can achieve data dimensionality reduction and update of principal components. We also introduce the concept of Squared Prediction Error (SPE) value and realize the abnormal detection of data through the combination of SPE value and data fusion algorithm. To ensure the accuracy and effectiveness of the algorithm, we design a regular-SPE hybrid model update strategy, which enables the principal component to be updated on demand when data anomalies are found. In addition, this strategy can significantly reduce resource consumption growth due to the data analysis architectures. Practical datasets-based simulations have confirmed that the proposed algorithm can perform data fusion and exception processing in real-time on resource-constrained devices; Our model update strategy can reduce the overall system resource consumption while ensuring the accuracy of the algorithm.

• Smart Structures and Systems
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• v.24 no.5
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• pp.567-585
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• 2019

In the past two decades, structural health monitoring (SHM) systems have been widely installed on various civil infrastructures for the tracking of the state of their structural health and the detection of structural damage or abnormality, through long-term monitoring of environmental conditions as well as structural loadings and responses. In an SHM system, there are plenty of sensors to acquire a huge number of monitoring data, which can factually reflect the in-service condition of the target structure. In order to bridge the gap between SHM and structural maintenance and management (SMM), it is necessary to employ advanced data processing methods to convert the original multi-source heterogeneous field monitoring data into different types of specific physical indicators in order to make effective decisions regarding inspection, maintenance and management. Conventional approaches to data analysis are confronted with challenges from environmental noise, the volume of measurement data, the complexity of computation, etc., and they severely constrain the pervasive application of SHM technology. In recent years, with the rapid progress of computing hardware and image acquisition equipment, the deep learning-based data processing approach offers a new channel for excavating the massive data from an SHM system, towards autonomous, accurate and robust processing of the monitoring data. Many researchers from the SHM community have made efforts to explore the applications of deep learning-based approaches for structural damage detection and structural condition assessment. This paper gives a review on the deep learning-based SHM of civil infrastructures with the main content, including a brief summary of the history of the development of deep learning, the applications of deep learning-based data processing approaches in the SHM of many kinds of civil infrastructures, and the key challenges and future trends of the strategy of deep learning-based SHM.

• Nuclear Engineering and Technology
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• v.56 no.6
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• pp.2220-2238
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• 2024

As a typical active equipment, pump machinery is widely used in nuclear power plants. Although the mechanism of pump machinery in nuclear power plants is similar to that of conventional pumps, the safety and reliability requirements of nuclear pumps are higher in complex operating environments. Once there is significant performance degradation or failure, it may cause huge security risks and economic losses. There are many pumps mechanical parameters, and it is very important to explore the correlation between multi-dimensional variables and condition. Therefore, a condition monitoring model based on Deep Denoising Autoencoder (DDAE) is constructed in this paper. This model not only ensures low false positive rate, but also realizes early abnormal monitoring and location. In order to alleviate the influence of parameter time-varying effect on the model in long-term monitoring, this paper combined equidistant sampling strategy and DDAE model to enhance the monitoring efficiency. By using the simulation data of reactor coolant pump and the actual centrifugal pump data, the monitoring and positioning capabilities of the proposed scheme under normal and abnormal conditions were verified. This paper has important reference significance for improving the intelligent operation and maintenance efficiency of nuclear power plants.

• Animal cells and systems
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• v.16 no.1
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• pp.50-56
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• 2012

Kelp grouper ($Epinephelus$ $bruneus$ Bloch 1793) is a commercially important fish in Korea. In recent years, the catch of kelp grouper in the coastal waters of Korea has significantly declined. Despite its importance, little is known about its genetic diversity and conservation efforts are hampered. In this study, we isolated and characterized 12 microsatellite loci using an enrichment method based on magnetic/biotin capture of microsatellite sequences from a size-selected genomic library. All loci were readily amplified and contained TG/CA denucleotide repeats. To characterize each locus, 30 individuals from a natural E. bruneus population in the coastal waters of Jeju Island, Korea, were genotyped. All loci except three, KEm118, KEm154, and KEm219, were polymorphic, with an average of 8.1 alleles per locus (range 2-18). The mean observed and expected heterozygosities were 0.47 (range 0.19-1.00) and 0.61 (range 0.29-0.92), respectively. A significant deviation from Hardy-Weinberg equilibrium was observed at three loci (KEm134, KEm184, and KEm283). These findings will be useful for effective monitoring and management of genetic variation of kelp grouper as well as for the implementation of a fisheries conservation program.

• International Journal of Computer Science & Network Security
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• v.22 no.2
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• pp.47-56
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• 2022

The article defines the principles of formation of digital marketing strategy of enterprises in the conditions of intensification of competition on the international market. The stages of development of digital marketing strategy of enterprises in the conditions of intensification of competition in the international market are substantiated, which includes: setting goals, which envisages observance of the principles of SMART-scheme; product or service analysis; monitoring of competitors; analytics of definition and segmentation of the target audience of the enterprise; selection of digital marketing tools and channels for promotion on the international market of products or services; formation of a unique, unique trade offer, selection of indicators for evaluating the effectiveness of digital marketing strategy and its tools. It is proved that according to the principle of SMART method of goal setting it is necessary that the goals have: specificity, measurability, achievability, relevance, achievement of the goal should be limited in time, have specific deadlines. To increase the effectiveness of digital marketing strategy, it is necessary to analyze the internal and external environment using the method of SWOT-analysis, the advantage of which is a comprehensive assessment of the company, competitors and the industry as a whole in the face of competition in the international market. The main indicators of evaluation of the effectiveness of digital marketing strategy in the conditions of intensification of competition on the international market are substantiated.

• Journal of the Korea Society of Computer and Information
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• v.24 no.11
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• pp.99-107
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• 2019

The "Risk management" and "Security monitoring" activities for cyber security are deeply correlated in that they prepare for future security threats and minimize security incidents. In addition, it is effective to apply a pattern model that visually demonstrates to an administrator the threat to that information asset in both the risk management and the security system areas. Validated pattern models have long-standing "control chart" models in the traditional quality control sector, but lack the use of information systems in cyber risk management and security systems. In this paper, a cyber Security Risk Monitoring (SRM) system that integrates risk management and a security system was designed. The SRM presents a strategy for applying 'security control' using the pattern of 'control charts'. The security measures were integrated with the existing set of standardized security measures, ISMS, NIST SP 800-53 and CC. Using this information, we analyzed the warning trends of the cyber crisis in Korea for four years from 2014 to 2018 and this enables us to establish more flexible security measures in the future.

• Journal of Advanced Navigation Technology
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• v.28 no.1
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• pp.1-14
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• 2024

Global navigation satellite system (GNSS) providing position, navigation and timing (PNT) services consist of satellite, ground, and user systems. Monitoring stations, a key element of the ground segment, play a crucial role in continuously collecting satellite navigation signals for service provision and fault detection. These stations detect anomalies such as threats to the signal-in-space (SIS) of satellites, receiver issues, and local threats. They deliver received data and detection results to the master station. This paper introduces the main monitoring algorithms and measurement pre-processing processes for quality assessment and fault detection of received satellite signals in current satellite navigation system monitoring stations. Furthermore, it proposes a strategy for the development of components, architecture, and algorithms for the new regional navigation satellite system (RNSS) monitoring stations.

• Korean Journal of Construction Engineering and Management
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• v.10 no.6
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• pp.28-39
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• 2009

Recently, it has been an issue on BPM(Business Process Management, below BPM), which is a sort of business management methods that secures agility and flexibility through sustainable improving and monitoring in a rapid-changing environment. To introduce BPM to construction company we need to set up a procedure for objective, define criteria according to the business structure defined by BPA(Business Process Architecture, below BPA) and analyze works and then select targets. Those BPM target works need to have a close relationship with corporate strategy and to support realizing corporate value. Therefore, this paper will study BPM Target works of construction companies for an effective introduction BPM through questioning from working-level staff. In addition, it will analyze their types and corporate core strategy and BPM target works, then study the main strategy according to BPM target types. And also, this study is expected to help construction companies to choose the business for BPM adoption through analyzing current situation and strategy for business selection when adopting BPM.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.12
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• pp.7025-7039
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• 2014

Focal companies (hereafter called buyers) adopt outsourcing practices from a supply chain management strategy to be competitive. Buyers face the bridge transfer after outsourcing contracts, and the monitoring practices would be the only control mechanism left to prevent losing control over the suppliers. This study suggests the set of monitoring practices (i.e., capability, activity and outcome monitoring) as the independent variables to enhance the buyer-supplier collaboration and supplier's performance. In addition the buyer's efforts of monitoring are assumed to influence the buyer's shop floor productivity mediated by the supplier's performance and buyer-supplier collaboration. The results showed that the monitoring practices are meaningful antecedents to the supplier's performance and buyer-supplier collaboration, which fully mediates between the monitoring practices and buyer's shop floor productivity. The mediating role of the buyer-supplier collaboration between activity monitoring and shop floor productive has been rejected, because the negative effect of activity monitoring on buyer-supplier collaboration conflicts with the positive impact of buyer-supplier collaboration on shop floor productive. The theoretical contribution and managerial implications with limitations have been discussed.