• Convergence Security Journal
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• v.20 no.4
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• pp.135-141
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• 2020

The Ministry of National Defense is strengthening the power and capacity of cyber operations as cyber protection training is conducted. However, considering the level of enemy cyber attack capability, the level of cyber defense capability of the ministry of national defense is significantly low and the protection measures and response system for responding to cyber threats to military networks are not clearly designed, falling short of the level of cyber security capabilities of the public and private sectors. Therefore, this paper is to investigate and verify the establishment of a military internal network vulnerability mitigation system that applies the intention of attackers, tactics, techniques and procedures information (ATT&CK Framework), identified military internal network main threat information, and military information system security requirements with military specificity as factors that can establish a defense network vulnerability mitigation system by referring to the domestic and foreign cyber security framework It has the advantage of having.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.45 no.2
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• pp.37-47
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• 2022

The Act on the Punishment of Serious Accidents to Prevent Large-scale Disasters, including Ferry Sewol and Taean Thermal Power Plant, passed the National Assembly on January 8, 2021, and has been in effect since January 27, 2022. However, the law, in which the representative of the headquarters is unlimitedly responsible for each worker's accident, is somewhat unreasonable at a time when a company owns dozens to hundreds of construction sites due to the nature of the construction industry. I agree with the purpose of enacting the law to reduce chronic serious accidents at construction sites, but it is necessary to carefully reconsider the implementation of the law in that punishment alone cannot achieve industrial safety. Previous studies focused on revising the Occupational Safety and Health Act, but there are few studies on the impact on the construction industry after the implementation of the Serious Accident Act. Therefore, this study attempts to derive problems related to the application of the Serious Accident Act and present improvement measures. To this end, after analyzing previous studies, SWOT analysis was performed by applying the Delphi method to derive strengths, weaknesses, opportunities, and threats. In addition, the results of two surveys of safety experts such as public institutions, academia, and companies were reflected, and its countermeasures were presented as follows. S/O strategy: establishing on-site execution capabilities of health and safety management system; W/O strategy: expanding legal and system execution checks; S/T strategy: establishing a risk response system; W/T strategy: expanding consulting by external specialized institutions

• Journal of the Korea Society of Computer and Information
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• v.27 no.11
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• pp.287-294
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• 2022

The purpose of this study is to define the concept of value-added services on online music platforms, put forward a model of users' willingness to use value-added services on online music platforms, and explore the way its influencing factors affect users' willingness to use. This study is based on the stimulus-response model, combined with the characteristics of online music service platforms, using information value, social value, and entertainment value as independent variables, using flow experience as a mediating variable, and self-awareness as a moderator variable, and then researches on the use of users. influence of will. Empirical analysis was carried out in this study using SPSS and AMOS statistical analysis tools. It is verified that the value-added services of online music platforms have a positive and positive impact on consumers' flow experience and usage intention. This research can fill in the theoretical defects of online music platform service, which has positive and important significance for music platform operators to improve their service capabilities and improve their income.

• Steel and Composite Structures
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• v.47 no.2
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• pp.167-184
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• 2023

In this study, a new recentering friction device (RFD) to retrofit steel moment frame structures is introduced. The device provides both self-centering and energy dissipation capabilities for the retrofitted structure. A hybrid performance-based seismic design procedure considering multiple limit states is proposed for designing the device and the retrofitted structure. The design of the RFD is achieved by modifying the conventional performance-based seismic design (PBSD) procedure using computational intelligence techniques, namely, genetic algorithm (GA) and artificial neural network (ANN). Numerous nonlinear time-history response analyses (NLTHAs) are conducted on multi-degree of freedom (MDOF) and single-degree of freedom (SDOF) systems to train and validate the ANN to achieve high prediction accuracy. The proposed procedure and the new RFD are assessed using 2D and 3D models globally and locally. Globally, the effectiveness of the proposed device is assessed by conducting NLTHAs to check the maximum inter-story drift ratio (MIDR). Seismic fragilities of the retrofitted models are investigated by constructing fragility curves of the models for different limit states. After that, seismic life cycle cost (LCC) is estimated for the models with and without the retrofit. Locally, the stress concentration at the contact point of the RFD and the existing steel frame is checked being within acceptable limits using finite element modeling (FEM). The RFD showed its effectiveness in minimizing MIDR and eliminating residual drift for low to mid-rise steel frames models tested. GA and ANN proved to be crucial integrated parts in the modified PBSD to achieve the required seismic performance at different limit states with reasonable computational cost. ANN showed a very high prediction accuracy for transformation between MDOF and SDOF systems. Also, the proposed retrofit showed its efficiency in enhancing the seismic fragility and reducing the LCC significantly compared to the un-retrofitted models.

• Journal of Korean Public Health Nursing
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• v.37 no.2
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• pp.247-260
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• 2023

Purpose: The purpose of this study was to gain an in-depth understanding of the characteristics and competencies of practice experienced by public health center nurses(PHNs) during the early response phase of the coronavirus disease 2019(COVID-19) pandemic. Methods: PHNs were recruited from public health centers(PHC) in ten cities in Korea, using purposive sampling. They participated in semi-structured, in-depth interviews from December 21, 2020, to February 18, 2021. The interviews were transcribed verbatim and analyzed using qualitative content analysis. Results: Three themes and nine categories were drawn from the findings. The three themes that emerged from the data analysis were as follows: 'Handling expanding work scope and overwhelming workload beyond prepared competencies, willing to go anywhere.', 'Performing tasks of cooperation and communication required in the disaster management administrative system.', 'Demonstrated proficiency in clinical nursing practices, but recognized the need for further development of leadership and administrative capabilities.' Conclusions: The experiences of the subjects' have implications for the development of content for community nursing education that cultivates basic competencies to respond to real pandemic situations during undergraduate education. It is proposed that it would be necessary to establish a support system for developing specialized competencies in public health nursing.

• Nuclear Engineering and Technology
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• v.55 no.9
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• pp.3409-3416
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• 2023

Licensing the next-generation of nuclear reactor designs requires extensive use of Modeling and Simulation (M&S) to investigate system response to many operational conditions, identify possible accidental scenarios and predict their evolution to undesirable consequences that are to be prevented or mitigated via the deployment of adequate safety barriers. Deep Learning (DL) and Artificial Intelligence (AI) can support M&S computationally by providing surrogates of the complex multi-physics high-fidelity models used for design. However, DL and AI are, generally, low-fidelity 'black-box' models that do not assure any structure based on physical laws and constraints, and may, thus, lack interpretability and accuracy of the results. This poses limitations on their credibility and doubts about their adoption for the safety assessment and licensing of novel reactor designs. In this regard, Physics Informed Neural Networks (PINNs) are receiving growing attention for their ability to integrate fundamental physics laws and domain knowledge in the neural networks, thus assuring credible generalization capabilities and credible predictions. This paper presents the use of PINNs as surrogate models for accidental scenarios simulation in Nuclear Power Plants (NPPs). A case study of a Loss of Heat Sink (LOHS) accidental scenario in a Nuclear Battery (NB), a unique class of transportable, plug-and-play microreactors, is considered. A PINN is developed and compared with a Deep Neural Network (DNN). The results show the advantages of PINNs in providing accurate solutions, avoiding overfitting, underfitting and intrinsically ensuring physics-consistent results.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.3
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• pp.161-166
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• 2023

In recent years, new and variant hacking of binary codes has increased, and the limitations of techniques for detecting malicious codes in source programs and defending against attacks are often exposed. Advanced software security vulnerability detection technology using machine learning and deep learning technology for binary code and defense and response capabilities against attacks are required. In this paper, we propose a malware clustering method that groups malware based on the characteristics of the taint information after entering dynamic taint information by tracing the execution path of binary code. Malware vulnerability detection was applied to a three-layered Few-shot learning model, and F1-scores were calculated for each layer's CPU and GPU. We obtained 97~98% performance in the learning process and 80~81% detection performance in the test process.

• Korea Trade Review
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• v.43 no.4
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• pp.177-217
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• 2018

The purpose of this study is to classify the types of internationalization strategies utilized by Korean ventures and to examine whether there is a significant relationship between these types and internationalization performances. Specifically we tested whether there is a good feasibility through empirical analysis of the study model constructed through the following process. As a criterion of typification, the capability of international entrepreneurship and the capability of effectuation of a venture were chosen, and a model in which those three types exist based on the capabilities is established. The characteristics of each type and the contents of internationalization strategy are explained and empirical analysis is conducted. We also test whether there are significant differences in internationalization performance for each type. As a result of the cluster analysis, we concluded that there are three types : pioneer, careful preparation and passive response. In addition, these three types have significant differences in the levels of performances of reputation in foreign markets and the accumulation of knowledge in international management. This implies significant differences among the performances of each type of ventures according to their internationalization strategy positions. Therefore, the type of venture should be considered when a venture establishes its internationalization strategy and governments set supporting policy for venture companies.

• Convergence Security Journal
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• v.22 no.5
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• pp.145-154
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• 2022

Recently, the widespread proliferation and high sophistication of botnets are having serious consequences not only for enterprises and users, but also for cyber warfare between countries. Therefore, research to detect botnets is steadily progressing. However, the DGA-based botnet has a high detection rate with the existing signature and statistics-based technology, but also has a high limit in the false positive rate. Therefore, in this paper, we propose a detection model using text-based n-gram to detect DGA-based botnets. Through the proposed model, the detection rate, which is the limit of the existing detection technology, can be increased and the false positive rate can also be minimized. Through experiments on large-scale domain datasets and normal domains used in various DGA botnets, it was confirmed that the performance was superior to that of the existing model. It was confirmed that the false positive rate of the proposed model is less than 2 to 4%, and the overall detection accuracy and F1 score are both 97.5%. As such, it is expected that the detection and response capabilities of DGA-based botnets will be improved through the model proposed in this paper.

• Journal of English Language & Literature
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• v.57 no.6
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• pp.1111-1130
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• 2011

Reading postmodern texts certainly situates readers in roles different from the ones we have been used to. Recently, postmodern metafiction forms a significant body of children's literature that is intended to challenge and transform the conventions of books in the digital age. While many studies have been done as to how child readers have capabilities to appreciate and interpret postmodern metafiction picture books, few studies on teachers and preservice teachers' reactions are not readily available. The role of teachers and preservice teachers are crucial for child readers to have access to affluent reading resources. This study discusses how preservice teachers read and respond to postmodern metafiction picture books using a deconstructive approach by means of binary opposites. Data was collected with 14 preservice teachers as to their likes/dislikes, reading levels, and reading paths about postmodern metafiction picture books. Expected pedagogical implications for literacy and language education were requested to address in their reading diaries and response papers. With their likes/ dislikes, since binary opposites always imply the hierarchy of power and value, the likes is apparently more valued and appreciated over their dislikes. This differentiated values are discussed in more detail with three recurring themes-Education, Morals and Behavior, and Tradition. With reading levels, there seems to be a gap existing between the authors' implied reader and literary critics' and the preservice teachers' ideal readers for the postmodern metafiction picture books. Although many studies have already revealed young readers' capability of appreciating postmodern metafiction, it depends a lot more on the teachers and preservice teachers whether children's right to have access to affluent literacy resources is respected or not. Preservice teachers' awareness of the potential of postmodern metafiction will work as an initial step to bring and realize the new reading path and new literacies in classrooms. By challenging metanarratives of children's literature, preservice teachers' readings of postmodern picture books reveals potentials to raise different reading paths and develop new literacies and other educational implications.