• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.1
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• pp.126-142
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• 2023

The purpose of this study is to develop unmanned traffic enforcement equipment and standard specifications for the prevention of traffic accidents and violations of the two-wheeled vehicle laws. To this end, we conducted a review of the problems and new technologies of the currently operating unmanned traffic enforcement equipment on two-wheeled vehicles. And through a survey, the feasibility of introducing unmanned traffic enforcement equipment for two-wheeled vehicles and the current status of technology were investigated. In addition, the two-wheeled vehicle enforcement function was implemented through field tests of the development equipment, and the addition of enforcement targets and the number recognition rate were improved through performance improvement. Based on the results of field experiments and performance evaluation, performance standards for unmanned two-wheeled vehicle traffic enforcement equipment were prepared, and in the communication protocol, two-wheeled vehicle-related matters were newly composed in the vehicle classification code and violation items to develop standards.

• Nuclear Engineering and Technology
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• v.54 no.12
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• pp.4809-4818
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• 2022

The decommissioning project of a nuclear facility is a large-scale process that is expected to take about 15 years or longer. The range of risks to be considered is large and complex, then, it is expected that various risks will arise in decision-making by area during the project. Therefore, in this study, the risk family derived from the Decommissioning Risk Management (DRiMa) project was reconstructed into a decommissioning project risk profile suitable for the Kori Unit 1. Two criteria of uncertainty and importance are considered in order to prioritize the selected 26 risks of decommissioning project. The uncertainty is scored according to the relevant laws and decommissioning plan preparation guidelines, and the project importance is scored according to the degree to which it primarily affects the triple constraints of the project. The results of risks are divided into high, medium, and low. Among them, 10 risks are identified as medium level and 16 risks are identified as low level. 10 risks, which are medium levels, are classified in five categories: End state of decommissioning project, Management of waste and materials, Decommissioning strategy and technology, Legal and regulatory framework, and Safety. This study is a preliminary assessment of the risk of the decommissioning project that could be considered in the preparation stage. Therefore, we expect that the project risks considered in this study can be used as an initial data for reevaluation by reflecting the detail project progress in future studies.

• Korea Trade Review
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• v.42 no.2
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• pp.297-318
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• 2017

This study reviews the origin verification system of China via literature research and analyzes cases of Korean exports origin disapproved of Chinese customs clearance, to provide origin verification strategy recommendations for Korean companies exporting to China under Korea-China FTA. We reviewed the provisions of Chinese rules of origin and analyzed origin disapproved cases gathered from various presentations. The main results of the study have the following implications; First, the customs authority needs to establish a consultation channel with the customs authority of China, and origin certification issuing agencies should provide exporters with consulting services in the certificate issuing stage to reduce verification risk. Second, exporters need to pay attention to the formal requirements of the proof of origin, utilize the advance rulings program of differences in classification of items between Korea and China, and monitor regulatory change in China.

• Journal of the Korean Society for information Management
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• v.40 no.2
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• pp.243-262
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• 2023

In the rapidly developing information technology environment, information management organizations need to effectively evaluate their digital maturity and clarify the direction of improvement to effectively respond to rapidly changing environments. This study derived weights for the digital curation maturity model developed by KISTI from the perspective of digital transformation to facilitate effective evaluation and direction setting of information management organizations. Relative importance was derived as a weight in the major and middle categories of the model through the AHP technique. Summarizing the results, when the major categories of the entire model are measured on the basis of 100 points, technology is 27 points, data is 24 points, strategy is 19 points, organization (manpower) is 16 points, and (social) influence is calculated as 14 points. In addition, weights for each subcategory were presented for each major classification based on a perfect score of 100 points. It is expected that a more objective and reasonable evaluation will be possible by applying the weights for each area derived from this study to the digital transformation maturity evaluation model.

• Journal of Chest Surgery
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• v.56 no.4
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• pp.264-271
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• 2023

Background: The optimal management strategy for aortoiliac occlusive disease (AIOD) remains debatable. This study compared early and late outcomes between direct surgical bypass and kissing stents for AIOD treatment. Methods: We retrospectively reviewed data, including age, sex, risk factors, comorbidities, symptoms, TransAtlantic Inter-Society Consensus (TASC) II classification, operation time, perioperative complications, in-hospital mortality, and length of hospital stay, from a cohort of 46 patients treated for AIOD (24 with kissing stents and 22 with direct surgical bypass) at Pusan National University Hostpital from January 2007 to December 2016. The primary, assisted primary, and secondary patency rates in both groups were compared. Results: The hospital stay (direct surgical bypass vs. kissing stents: 16.36±5.19 days vs. 9.08±10.88 days, p=0.007) and operation time (direct surgical bypass vs. kissing stents: 316.09±141.78 minutes vs. 99.54±37.95 minutes, p<0.001) were significantly shorter for kissing stents. Kaplan-Meier analysis revealed that the primary, assisted primary, and secondary patency rates in the direct surgical bypass group were 95.5%, 95.5%, and 95.5%, respectively, at 1 year; 86.4%, 86.4%, and 95.5% at 3 years; and 77.3%, 77.3%, and 95.5% at 5 years. The primary, assisted primary, and secondary patency rates in the kissing stent group were 100.0%, 100.0%, and 100.0%, respectively, at 1 year; 95.8%, 95.8%, and 100.0% at 3 years; and 95.8%, 95.8%, and 100.0% at 5 years. Conclusion: Except for special cases wherein endovascular revascularization is difficult, kissing stents are more advantageous for TASC II C and D lesions.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.4D
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• pp.493-504
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• 2008

Considerable effort has been made to improve construction processes through mechanization and robotization of current work. In this paper, the trend of research and development related to the construction machinery automation to improve the construction productivity has been reviewed. A classification system is proposed for automation of architectural and civil works. Then, the priority among the classified construction tasks for automation has been identified through the questionnaire study. Based on the priority for automation a comprehensive technology road map was also developed. The technology road map suggests the time frame to complete R&D work for the selected construction tasks and the core technology required for automation of the selected tasks. Such automation R&D road map for construction machinery can be utilized as a milestone in setting up the R&D strategy in the construction industry.

• International Journal of Computer Science & Network Security
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• v.23 no.11
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• pp.99-109
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• 2023

The darknet is frequently referred to as the hub of illicit online activity. In order to keep track of real-time applications and activities taking place on Darknet, traffic on that network must be analysed. It is without a doubt important to recognise network traffic tied to an unused Internet address in order to spot and investigate malicious online activity. Any observed network traffic is the result of mis-configuration from faked source addresses and another methods that monitor the unused space address because there are no genuine devices or hosts in an unused address block. Digital systems can now detect and identify darknet activity on their own thanks to recent advances in artificial intelligence. In this paper, offer a generalised method for deep learning-based detection and classification of darknet traffic. Furthermore, analyse a cutting-edge complicated dataset that contains a lot of information about darknet traffic. Next, examine various feature selection strategies to choose a best attribute for detecting and classifying darknet traffic. For the purpose of identifying threats using network properties acquired from darknet traffic, devised a hybrid deep learning (DL) approach that combines Recurrent Neural Network (RNN) and Bidirectional LSTM (BiLSTM). This probing technique can tell malicious traffic from legitimate traffic. The results show that the suggested strategy works better than the existing ways by producing the highest level of accuracy for categorising darknet traffic using the Black widow optimization algorithm as a feature selection approach and RNN-BiLSTM as a recognition model.

• Asia pacific journal of information systems
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• v.34 no.1
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• pp.150-190
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• 2024

This article proposes a framework to elucidate the structural dynamics of the generative AI ecosystem. It also outlines the practical application of this proposed framework through illustrative policies, with a specific emphasis on the development of the Korean generative AI ecosystem and its implications of platform strategies at AI platform-squared. We propose a comprehensive classification scheme within generative AI ecosystems, including app builders, technology partners, app stores, foundational AI models operating as operating systems, cloud services, and chip manufacturers. The market competitiveness for both app builders and technology partners will be highly contingent on their ability to effectively navigate the customer decision journey (CDJ) while offering localized services that fill the gaps left by foundational models. The strategically important platform of platforms in the generative AI ecosystem (i.e., AI platform-squared) is constituted by app stores, foundational AIs as operating systems, and cloud services. A few companies, primarily in the U.S. and China, are projected to dominate this AI platform squared, and consequently, they are likely to become the primary targets of non-market strategies by diverse governments and communities. Korea still has chances in AI platform-squared, but the window of opportunities is narrowing. A cautious approach is necessary when considering potential regulations for domestic large AI models and platforms. Hastily importing foreign regulatory frameworks and non-market strategies, such as those from Europe, could overlook the essential hierarchical structure that our framework underscores. Our study suggests a clear strategic pathway for Korea to emerge as a generative AI powerhouse. As one of the few countries boasting significant companies within the foundational AI models (which need to collaborate with each other) and chip manufacturing sectors, it is vital for Korea to leverage its unique position and strategically penetrate the platform-squared segment-app stores, operating systems, and cloud services. Given the potential network effects and winner-takes-all dynamics in AI platform-squared, this endeavor is of immediate urgency. To facilitate this transition, it is recommended that the government implement promotional policies that strategically nurture these AI platform-squared, rather than restrict them through regulations and stakeholder pressures.

• Journal of the Korean Society of Physical Medicine
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• v.19 no.1
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• pp.95-105
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• 2024

PURPOSE: This study aimed to utilize the International Classification of Functioning, Disability, and Health (ICF) tool to identify a problem list and explore intervention effects using proprioceptive neuromuscular facilitation (PNF) for improving the crosswalk performance of patients who have undergone a bilateral hip arthroplasty. METHODS: The subject of this study was a 43-year-old male who had undergone a bilateral hip arthroplasty. To address the subject's functional status, a clinical decision-making process was carried out in the order of examination, evaluation, diagnosis, prognosis, intervention, and outcome. Patient information during the examination was collected using the ICF core set. The evaluation involved listing the items of each problem using the ICF assessment sheet and identifying the interaction between activity limitations and the impairment level. The diagnosis explicitly described the causal relationships derived from the evaluation using ICF terminology. The prognosis presented activity goals, body function, and structured goals in terms of the activity and participation levels that needed to be achieved for an individual's functional status. The intervention approached problems through the four components of the PNF philosophy, namely basic principles and procedures, techniques, and patterns, in an indirect-direct-task sequence. Results were compared before and after the intervention using the ICF evaluation display. RESULTS: The results of the study showed that the primary activity limitation, which was the walking time across the crosswalk, showed improvement, and the trunk's counter rotation and the weight-bearing capacity of both the lower limbs, which were impairment level indicators, were enhanced. CONCLUSION: This study suggests that PNF intervention strategies will serve as a positive approach for improving crosswalk walking in patients with bilateral hip arthroplasty.

• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.139-160
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• 2017

Technology commercialization creates effective economic value by linking the company's R & D processes and outputs to the market. This technology commercialization is important in that a company can retain and maintain a sustained competitive advantage. In order for a specific technology to be commercialized, it goes through the stage of technical planning, technology research and development, and commercialization. This process involves a lot of time and money. Therefore, the duration and cost of technology commercialization are important decision information for determining the market entry strategy. In addition, it is more important information for a technology investor to rationally evaluate the technology value. In this way, it is very important to scientifically estimate the duration and cost of the technology commercialization. However, research on technology commercialization is insufficient and related methodology are lacking. In this study, we propose an evaluation model that can estimate the duration and cost of R & D technology commercialization for small and medium-sized enterprises. To accomplish this, this study collected the public data of the National Science & Technology Information Service (NTIS) and the survey data provided by the Small and Medium Business Administration. Also this study will develop the estimation model of commercialization duration and cost of R&D performance on using these data based on the market approach, one of the technology valuation methods. Specifically, this study defined the process of commercialization as consisting of development planning, development progress, and commercialization. We collected the data from the NTIS database and the survey of SMEs technical statistics of the Small and Medium Business Administration. We derived the key variables such as stage-wise R&D costs and duration, the factors of the technology itself, the factors of the technology development, and the environmental factors. At first, given data, we estimates the costs and duration in each technology readiness level (basic research, applied research, development research, prototype production, commercialization), for each industry classification. Then, we developed and verified the research model of each industry classification. The results of this study can be summarized as follows. Firstly, it is reflected in the technology valuation model and can be used to estimate the objective economic value of technology. The duration and the cost from the technology development stage to the commercialization stage is a critical factor that has a great influence on the amount of money to discount the future sales from the technology. The results of this study can contribute to more reliable technology valuation because it estimates the commercialization duration and cost scientifically based on past data. Secondly, we have verified models of various fields such as statistical model and data mining model. The statistical model helps us to find the important factors to estimate the duration and cost of technology Commercialization, and the data mining model gives us the rules or algorithms to be applied to an advanced technology valuation system. Finally, this study reaffirms the importance of commercialization costs and durations, which has not been actively studied in previous studies. The results confirm the significant factors to affect the commercialization costs and duration, furthermore the factors are different depending on industry classification. Practically, the results of this study can be reflected in the technology valuation system, which can be provided by national research institutes and R & D staff to provide sophisticated technology valuation. The relevant logic or algorithm of the research result can be implemented independently so that it can be directly reflected in the system, so researchers can use it practically immediately. In conclusion, the results of this study can be a great contribution not only to the theoretical contributions but also to the practical ones.