• Nuclear Engineering and Technology
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• 제48권1호
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• pp.144-152
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• 2016

Human capabilities, such as technical/nontechnical skills, have begun to be recognized as crucial factors for nuclear safety. One of the most common ways to improve human capabilities in general is training. The nuclear industry has constantly developed and used training as a tool to increase plant efficiency and safety. An integrated training framework was suggested for one of those efforts, especially during simulation training sessions of nuclear power plant operation teams. The developed training evaluation methods are based on measuring the levels of situation awareness of teams in terms of the level of shared confidence and consensus as well as the accuracy of team situation awareness. Verification of the developed methods was conducted by analyzing the training data of real nuclear power plant operation teams. The teams that achieved higher level of shared confidence showed better performance in solving problem situations when coupled with high consensus index values. The accuracy of nuclear power plant operation teams' situation awareness was approximately the same or showed a similar trend as that of senior reactor operators' situation awareness calculated by a situation awareness accuracy index (SAAI). Teams that had higher SAAI values performed better and faster than those that had lower SAAI values.

• Asian Journal of Innovation and Policy
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• 제11권1호
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• pp.87-109
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• 2022

The study attempts to examine the system-building activities of scientific institutions in developing the Molecular Diagnostic (MDs) Innovation System in India. Scientific Institutions are the precursor of any technological development with their capabilities in generating new ideas. MDs are advanced and accurate diagnostic technology with considerable scope to serve the diagnostic needs and requirements of the healthcare system. We adopted a System framework and analyzed the development of MDs in terms of the Technological Innovation System (TIS) functions, and the systematic challenges are assessed through the System Failure Framework (SFF). Based on the secondary and primary survey of prominent science base actors, the study finds that the role of government is crucial for facilitating technological development within a science base through the mobilization of resources. In India, the MDs technological development gained significant momentum over the last decade with the development of specialized human resources and dedicated research institutes. However, we do find that the innovative capabilities in attaining need-based TIS are sub-optimal owning to the specific diagnostic needs of highly burdened diseases in the society. The system analysis reveals that the TIS functions are underperforming because of the absence of a well-defined funding mechanism and goal-oriented targeted policy regime of the government. Since MDs have a transformative effect on the present healthcare system, we argue that the government has to address the system-based challenges and issues for developing a need-based technological innovation system for MDs in the country.

• 한국유기농업학회지
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• 제31권4호
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• pp.259-289
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• 2023

This study analyzed farmers' and experts' perceptions of the Agricultural Income Survey (AIS) conducted by the Rural Development Administration and estimated its socioeconomic value. The research surveyed 104 farmers in Gyeongsangbuk-do and Jeollanam-do. To estimate the AIS's socioeconomic value, this study examined public information projects in the field of agriculture and public information, proposing an estimation methodology based on prior research. The socioeconomic value of the AIS was calculated in three stages (information generation, collection and analysis, and utilization) using the replacement cost and contingent valuation methods. In 2020, the estimated socioeconomic value of the AIS ranged from a minimum of KRW 631.2 billion to a maximum of KRW 799.1 billion per year. To improve the socioeconomic value of the AIS, it is important to booster awareness, expand sample sizes for more reliable data, increase manpower and budget, refine survey questions, and enhance analyzing capabilities. And it's crucial to foster cooperation with surveyed farms, promote collaboration among investigative agencies, improve investigator skills, and strengthen management capabilities to facilitate information dissemination.

• 산경연구논집
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• 제15권7호
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• pp.19-28
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• 2024

Purpose: The objective of this research was to investigate how blockchain ventures can optimize their wealth through Initial Coin Offerings (ICOs). Drawing upon signal theory, this study examined the impact of technological capabilities on the performance of ICOs in blockchain ventures. Given the highly technical nature of companies involved in ICOs, the technical proficiency of venture companies can have a significant influence on the success of ICOs. Specifically, three potential indicators of technological capability - patents, white papers, and source code - were analyzed. Research design, data and methodology: To accomplish this, a database was constructed by coding the relevant variables from various sources for 514 companies that launched ICOs. This study conducted hierarchical regression analysis for the hypotheses test. Results: The results indicated that a blockchain venture with a patent had a positive effect on the performance of the ICO. Additionally, publishing source code had a positive impact on ICO performance. Conclusions: This study identifies crucial factors for ICO success, emphasizing the importance of technological capabilities. Companies should enhance these to boost investor confidence, transparency, and outcomes. This research offers valuable insights for businesses and policymakers in the evolving cryptocurrency market, aiming to maximize ICO performance and success.

• International Journal of Internet, Broadcasting and Communication
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• 제16권3호
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• pp.221-227
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• 2024

In autonomous navigation systems, the need for fast and accurate image processing using deep learning and advanced sensor technologies is paramount. These systems rely heavily on the ability to process and interpret visual data swiftly and precisely to ensure safe and efficient navigation. Despite the critical importance of such capabilities, there has been a noticeable lack of research specifically focused on ship image classification for maritime applications. This gap highlights the necessity for more in-depth studies in this domain. In this paper, we aim to address this gap by presenting a comprehensive comparative study of ship image classification using two distinct neural network models: the Feedforward Neural Network (FNN) and the Convolutional Neural Network (CNN). Our study involves the application of both models to the task of classifying ship images, utilizing a dataset specifically prepared for this purpose. Through our analysis, we found that the Convolutional Neural Network demonstrates significantly more effective performance in accurately classifying ship images compared to the Feedforward Neural Network. The findings from this research are significant as they can contribute to the advancement of core source technologies for maritime autonomous navigation systems. By leveraging the superior image classification capabilities of convolutional neural networks, we can enhance the accuracy and reliability of these systems. This improvement is crucial for the development of more efficient and safer autonomous maritime operations, ultimately contributing to the broader field of autonomous transportation technology.

• Nuclear Engineering and Technology
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• 제56권7호
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• pp.2666-2675
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• 2024

This study explores the potential for tritium production in North Korea's 5MWe graphite-moderated reactor, a facility primarily associated with nuclear weapons material production. While existing research on these reactors has largely centered on plutonium, our focus shifts to tritium, a crucial element in boosted fission bombs. Utilizing the MCNP6 code for simulations, the results estimate that North Korea can possibly produce approximately 7-12 g of tritium annually. This translates to the potential production of 1-3 boosted fission bombs each year. By incorporating tritium production into assessments of North Korea's nuclear capabilities, our methodology provides insights into the dynamics of the country's nuclear force, revealing a more diversified and complex composition than previously assumed. The findings significantly aid policymakers, regulatory bodies, and researchers in comprehending potential proliferation risks associated with graphite-moderated reactors and in developing strategies to address the nuclear threat emanating from North Korea.

• 문화기술의 융합
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• 제10권4호
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• pp.1-15
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• 2024

우리는 현대 사회에서 중요한 역할을 하는 소상공인의 성공 요인을 깊이 있게 조사하고 분석하여, 그들의 경영 성과에 미치는 요인들을 명확하게 이해하려는 노력을 기울였다. 우리는 소상공인의 경영 역량, 정부 지원 서비스, 그리고 정책 지원 자금의 이용 여부를 주요 변수로 설정하였다. 우리의 연구 결과, 소상공인의 경영 역량과 정부 지원 서비스는 그들의 경영 성과에 긍정적인 영향을 미치는 것으로 나타났다는 사실을 발견하였다. 이는 소상공인들이 자신의 역량을 강화하고, 정부의 지원 서비스를 효율적으로 활용함으로써 경영 성과를 향상시킬 수 있음을 의미한다. 정책 지원 자금의 이용 여부는 정부 지원 서비스가 재무 성과에 미치는 영향에만 조절 효과를 보일 뿐, 다른 경영 성과에는 영향을 미치지 않는 것으로 나타났다. 정책 지원 자금의 이용이 필요하긴 하지만, 그 자체만으로는 충분하지 않으며, 다른 변수들과 복합적으로 작용해야 효과를 볼 수 있음을 시사한다. 우리의 연구는 소상공인의 성공을 위한 새로운 방향성을 제시하였다. 이 연구를 통해 소상공인 및 관련 정책 결정자들은 어떤 요인들이 소상공인의 경영 성과에 영향을 미치는지, 그리고 어떻게 이러한 요인들을 효과적으로 관리하고 활용할 수 있는지에 대해 깊은 통찰을 얻을 수 있을 것이다. 이 연구는 기업 경영 및 소상공인에 대한 학문적 연구에 중요한 기여를 하였다. 소상공인의 성공 요인에 대한 깊은 이해를 통해, 이들의 경영 성과를 향상시키는 데 도움이 될 수 있는 새로운 연구 방향성과 전략을 제시하였다. 이러한 노력은 소상공인의 사회적, 경제적 가치를 높이는 데 한걸음 더 나아가는 계기가 될 것이다.

• KIEE International Transactions on Power Engineering
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• 제11A권4호
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• pp.15-20
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• 2001

Power system stability is correlated with system structure, disturbances and operating conditions, and power flows on transmission lines are closely related with those conditions. This paper proposes a methodology to identify correlative power flows for power system transient and small-signal stability prediction. In transient stability sense, the Critical Clearing Time is used to select some dominant contingencies, and Transient Stability Prediction index is proposed for the quantitative comparison. For small-signal stability discusses a methodology to identify crucial transmission lines for stability prediction by introducing a sensitivity factor based on eigenvalue sensitivity technique. On-line monitoring of the selected lines enables to predict system stability in real-time. Also, a procedure to make a priority list of monitored transmission lines is proposed. The procedure is applied to a test system, and it shows capabilities of the proposed method.

• International Journal of Control, Automation, and Systems
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• 제1권1호
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• pp.1-10
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• 2003

This paper presents a high-precision magnetically levitated (maglev) stage to meet demanding motion specifications in the next-generation precision manufacturing and nanotechnology. Characterization of dynamic behaviors of such a motion stage is a crucial task. In this paper, we address the issues related to the stochastic modeling of the stage including transfer function identification, and noise/disturbance analysis and prediction. Provided are test results on precision dynamics, such as fine settling, effect of optical table oscillation, and position ripple. To deal with the dynamic coupling in the platen, we designed and implemented a multivariable linear quadratic regulator, and performed time-optimal control. We demonstrated how the performance of the current maglev stage can be improved with these analyses and experimental results. The maglev stage operates with positioning noise of 5 nm rms in $\chi$ and y, acceleration capabilities in excess of 2g(20 $m/s^2$), and closed-loop crossover frequency of 100 Hz.

• International Journal of Advanced Culture Technology
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• 제2권2호
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• pp.7-10
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• 2014

In order to develop smart grid communications infrastructure, a high level of interconnectivity and reliability among its nodes is required. Sensors, advanced metering devices, electrical appliances, and monitoring devices, just to mention a few, will be highly interconnected allowing for the seamless flow of data. Reliability and security in this flow of data between nodes is crucial due to the low latency and cyber-attacks resilience requirements of the Smart Grid. In particular, Artificial Intelligence techniques such as Fuzzy Logic, Bayesian Inference, Neural Networks, and other methods can be employed to enhance the security gaps in conventional IDSs. A distributed FPGA-based network with adaptive and cooperative capabilities can be used to study several security and communication aspects of the smart grid infrastructure both from the attackers and defensive point of view. In this paper, the vital issue of security in the smart grid is discussed, along with a possible approach to achieve this by employing FPGA based Radial Basis Function (RBF) network intrusion.