• Nuclear Engineering and Technology
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• v.45 no.1
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• pp.13-20
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• 2013

This paper looks at the Fukushima disaster from the perspective of resilience engineering, which replaces a search for causes with an understanding of how the system failed in its performance. Referring to the four resilience abilities of responding, monitoring, learning, and anticipating, the paper focuses on how inadequate engineering anticipation or risk assessment during the design, in combination with inadequate response capabilities, precipitated the disaster. One lesson is that systems such as nuclear power plants are complicated, not only in how they function during everyday or exceptional conditions, but also during their whole life cycle. System functions are intrinsically coupled synchronically and diachronically in ways that may affect the ability to respond to extreme conditions.

• Korea Journal of Hospital Management
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• v.14 no.2
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• pp.75-98
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• 2009

As the organizational environments are changing, organizational innovation has become a critical success factor for the healthcare organizations. Although there are lots of successful innovation cases in other industries, healthcare organization's management innovation cases are rare in Korea. This case study is focused on successful change process of a Maeumsarang psychiatric hospital. Main findings are: (a) virtuous cycle of healthcare service innovation and organizational innovation, (b) intensive training and learning, (c) usage of external resources, (d) high commitment HRM system, (e) CEO leadership, and (f) synchronization of planning and execution. Based on these findings, managerial implications are derived and future research directions are proposed.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.811-813
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• 1996

High impedance fault can not be easily detected by conventional method. But if it would not be detected and cleared quickly, it can result in fires, and electric shock. In this paper, neural network, which has learning capability, is used for high impedance fault detector. The potential of the neural network approach is demonstrated by simulation using KEPCO's measured data. The instantaneous values and frequency spectrum of current are respectively used as the inputs of neural networks. Also, the methods using combined data to exploit the advantage of each data are proposed. In this paper, back-propagation network(BPN) is used for high impedance fault detector and can use for high speed relay because it detects faults within 1 cycle.

• Journal of Fisheries and Marine Sciences Education
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• v.24 no.3
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• pp.416-423
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• 2012

Smartphone and Tablet PC has become a popular. So, various location-based service applications are being made in the field of advertising, games, and search. However, the location-based services application is lacking in the field of education. Therefore, this study proposes a Location-based service application for Tablet PC, which can be take advantage in school. The application was designed with these considerations in mind. First, the application to increase the participation of the students take the form of play. Second, participating students are influencing each other. Third, through the promotion of the cycle has allowed long-term operations. This application will be used usefully in an environment that students use a individual Tablet PC through the spread of e-textbooks.

• International journal of advanced smart convergence
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• v.9 no.4
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• pp.124-131
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• 2020

As users of internet-based software applications increase, functional and non-functional problems for software applications are quickly exposed to user reviews. These user reviews are an important source of information for software improvement. User review mining has become an important topic of intelligent software engineering. This study proposes a user review mining method for software improvement. User review data collected by crawling on the app review page is analyzed to check user satisfaction. It analyzes the sentiment of positive and negative that users feel with a machine learning method. And it analyzes user requirement issues through topic analysis based on structural topic modeling. The user review mining process proposed in this study conducted a case study with the a non-face-to-face video conferencing app. Software improvement through user review mining contributes to the user lock-in effect and extending the life cycle of the software. The results of this study will contribute to providing insight on improvement not only for developers, but also for service operators and marketing.

• Journal of Korea Multimedia Society
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• v.25 no.2
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• pp.157-165
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• 2022

As the stock market is affected by various circumstances including economic and political variables, predicting the stock market is considered a still open problem. When combined with corporate financial statement data analysis, which is used as fundamental analysis, and technical analysis with a short data generation cycle, there is a problem that the time domain does not match. Our proposed method, LSTE the operating profit and market outlook of a petrochemical company and estimates the sales and operating profit of the company, it was possible to solve the above-mentioned problems and improve the accuracy of stock price prediction. Extensive experiments on real-world stock data show that our method outperforms the 8.58% relative improvements on average w.r.t. accuracy.

• Proceedings of the Korean Society of Computer Information Conference
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• 2020.07a
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• pp.347-349
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• 2020

본 논문에서는 컴퓨팅 이미지 객체인식 시스템인 YOLO 성능 향상을 위한 효율적인 이미지 마킹 정책을 제안한다. 이 정책은 이미지 데이터를 통한 객체인식 학습 YOLO의 객체인식을 높이고 다른 객체와의 구분을 최대화하여 학습 모델의 성능을 높인다. YOLO의 성능을 최대화하기 위하여 YOLO의 학습을 몇 번 시킬 것인지 무엇을 객체로 인식시킬지 동적으로 할당한다. 이때 학습 싸이클에 따라 객체의 인식이 달라지며 어느 싸이클에서 가장 효율적인지, 왜 다른 객체를 같이 학습시켜야 하는지 중명한다. 본 논문에서는 YOLO의 싸이클과 다른 객체 학습에 있어서 최적의 객체인식 싸이클과 학습 성능 향상 면에서 우수함을 보인다.

• Molecules and Cells
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• v.47 no.1
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• pp.100006.1-100006.10
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• 2024

Nitric oxide (NO) serves as an evolutionarily conserved signaling molecule that plays an important role in a wide variety of cellular processes. Extensive studies in Drosophila melanogaster have revealed that NO signaling is required for development, physiology, and stress responses in many different types of cells. In neuronal cells, multiple NO signaling pathways appear to operate in different combinations to regulate learning and memory formation, synaptic transmission, selective synaptic connections, axon degeneration, and axon regrowth. During organ development, elevated NO signaling suppresses cell cycle progression, whereas downregulated NO leads to an increase in larval body size via modulation of hormone signaling. The most striking feature of the Drosophila NO synthase is that various stressors, such as neuropeptides, aberrant proteins, hypoxia, bacterial infection, and mechanical injury, can activate Drosophila NO synthase, initially regulating cellular physiology to enable cells to survive. However, under severe stress or pathophysiological conditions, high levels of NO promote regulated cell death and the development of neurodegenerative diseases. In this review, I highlight and discuss the current understanding of molecular mechanisms by which NO signaling regulates distinct cellular functions and behaviors.

• International Journal of Computer Science & Network Security
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• v.24 no.6
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• pp.109-118
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• 2024

The world today is advancing towards a digital solution for every indusial domain varying from advanced engineering and medicine to training and management. The supply cycles can only be boosted via an effective management of the warehouse and a stronger hold over the logistics and inventory insights. RFID technology has been an open source tool for various MNCs and corporal organization who have progressed along a considerable drift on the charts. RFID is a methodology of analysing the warehouse and logistic data and create useful information in line to the past trends and future forecasts. The method has a high tactical accuracy and has been seen providing up to 99.57% accurate insights for the future cycle, based on the organizational capabilities and available resources. This paper discusses the implementation of RFID on field and provides results of datasets retrieved from controlled data of a practical warehouse and logistics system.

• KIPS Transactions on Computer and Communication Systems
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• v.9 no.11
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• pp.256-264
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• 2020

Industrial Wireless Sensor Networks (IWSNs) is exploited to achieve various objectives such as improving productivity and reducing cost in the diversity of industrial application, and it has requirements such as low-delay and high reliability packet transmission. To accomplish the requirement, the network manager performs graph construction and resource allocation about network topology, and determines the transmission cycle and path of each node in advance. However, this network management scheme cannot treat mobile devices that cause continuous topology changes because graph reconstruction and resource reallocation should be performed as network topology changes. That is, despite the growing need of mobile devices in many industries, existing scheme cannot adequately respond to path failure caused by movement of mobile device and packet loss in the process of path recovery. To solve this problem, a network management scheme is required to prevent packet loss caused by mobile devices. Thus, we analyse the location and movement cycle of mobile devices over time using machine learning for predicting the mobility pattern. In the proposed scheme, the network manager could prevent the problems caused by mobile devices through performing graph construction and resource allocation for the predicted network topology based on the movement pattern. Performance evaluation results show a prediction rate of about 86% compared with actual movement pattern, and a higher packet delivery ratio and a lower resource share compared to existing scheme.