• The Journal of Internal Korean Medicine
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• v.44 no.3
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• pp.313-353
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• 2023

Objectives: Heart failure is a chronic disease with increasing prevalence rates despite advancements in medical technology. Korean medicine utilizes herbal prescriptions to treat heart failure, but little is known about the specific herbal medicines comprising the network of herbal prescriptions for heart failure. This study proposes a novel methodology that can efficiently develop prescriptions and facilitate experimental research on heart failure by utilizing existing databases. Methods: Herbal medicine prescriptions for heart failure were identified through a PubMed search and compiled into a Google Sheet database. NetMiner 4 was used for network analysis, and the individual networks were classified according to the herbal medicine classification system to identify trends. K-HERB NETWORK was utilized to derive related prescriptions. Results: Network analysis of heart failure prescriptions and herbal medicines using NetMiner 4 produced 16 individual networks. Uhwangcheongsim-won (牛黃淸心元), Gamiondam-tang (加味溫膽湯), Bangpungtongseong-san (防風通聖散), and Bunsimgi-eum (分心氣飮) were identified as prescriptions with high similarity in the entire network. A total of 16 individual networks utilized K-HERB NETWORK to present prescriptions that were most similar to existing prescriptions. The results provide 1) an indication of existing prescriptions with potential for use to treat heart failure and 2) a basis for developing new prescriptions for heart failure treatment. Conclusion: The proposed methodology presents an efficient approach to developing new heart failure prescriptions and facilitating experimental research. This study highlights the potential of network pharmacology methodology and its possible applications in other diseases. Further studies on network pharmacology methodology are recommended.

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.500-504
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• 1995

A neural network based upon the back propagation algorithm was designed and applied to acoustic power spectra of electrohydraulic total artificial hearts in order to diagnose mechanical failure of devices. The trained network distinguished spectra of the mechanically damaged device from those of the undamaged device with overall success rate of 63%. Moreover, the network correctly classified more than 70% of spectra in the frequency bands of 0-100 Hz and 700-950 Hz. Consequently, the neural network analysis was useful for the diagnosis of mechanical failure of a total artificial heart.

• Journal of Communications and Networks
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• v.16 no.5
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• pp.534-547
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• 2014

Large-scale failures resulting from natural disasters or intentional attacks are now causing serious concerns for communication network infrastructure, as the impact of large-scale network connection disruptions may cause significant costs for service providers and subscribers. In this paper, we propose a new framework for the analysis and prevention of network service disruptions in large-scale failure scenarios. We build dynamic deterministic and probabilistic models to capture the impact of regional failures as they evolve with time. A probabilistic failure model is proposed based on wave energy behaviour. Then, we develop a novel approach for preventive protection of the network in such probabilistic large-scale failure scenarios. We show that our method significantly improves uninterrupted delivery of data in the network and reduces service disruption times in large-scale regional failure scenarios.

• Advanced Composite Materials
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• v.18 no.3
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• pp.233-249
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• 2009

Safe installation and operation of high-pressure composite cylinders for hydrogen storage are of primary concern. It is unavoidable for the cylinders to experience temperature variation and significant thermal input during service. The maximum failure pressure that the cylinder can sustain is affected due to the dependence of composite material properties on temperature and complexity of cylinder design. Most of the analysis reported for high-pressure composite cylinders is based on simplifying assumptions and does not account for complexities like thermo-mechanical behavior and temperature dependent material properties. In the present work, a comprehensive finite element simulation tool for the design of hydrogen storage cylinder system is developed. The structural response of the cylinder is analyzed using laminated shell theory accounting for transverse shear deformation and geometric nonlinearity. A composite failure model is used to evaluate the failure pressure under various thermo-mechanical loadings. A back-propagation neural network (NNk) model is developed to predict the maximum failure pressure using the analysis results. The failure pressures predicted from NNk model are compared with those from test cases. The developed NNk model is capable of predicting the failure pressure for any given loading condition.

• Proceedings of the Korea Contents Association Conference
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• 2009.05a
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• pp.699-705
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• 2009

This paper reviews methods used to perform reliability and availability analysis of the network system composed by nodes and links. The combination of nodes and links forms virtual connections (VC). The failure of several VCs cause failure of whole network system. Petri Net models are used to analyze the reliability and availability. Stochastic reward nets (SRN) is an extension of stochastic Petri nets provides modelling facilities for network system analysis.

• Korean Management Science Review
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• v.11 no.1
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• pp.187-196
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• 1994

Time-Space-Time(T-S-T) switching network is modeled as a graceful degrading system. Call blocking probability is defined as a measure of performance. Several performance related measures are suggested under the presence of failure. An optimization model is proposed, which determines optimal values of system parameters of the switching network.

• Journal of the Korea Society for Simulation
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• v.13 no.2
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• pp.65-73
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• 2004

The capability to provide the network service must survive even if a significant network system element is disrupted. To sustain the network service under the system failure, network survivability mechanisms minimizing the impact of failures are needed. Also, since the mobile network has its unique characteristic, the survivability scheme for the vulnerability of the mobile network is required. This paper proposes a survivability scheme to support the reliable service of the wireless access point level (BS-base station system). By the survivability scheme, the mobile network can use an overlap BS of the cellular network architecture after a BS system failure. We analyze the performance of the proposed scheme using Markov model. Also, a computer simulation is used for the scheme analysis. The proposed scheme shows that the service of the mobile network can be provided under the BS system failure.

• Journal of information and communication convergence engineering
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• v.10 no.1
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• pp.11-20
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• 2012

In a marine ubiquitous sensor network (USN) system using expensive sensors in the harsh ocean environment, it is very important to discover failures and devise recovery techniques to deal with such failures. Therefore, in order to perform failure modeling, this study analyzes the USN-based real-time water quality monitoring service of the Gaduri Aqua Farms at Songdo Island of Yeosu, South Korea and devises methods of discovery and recovery of failure by classifying the types of failure into system element failure, communication failure, and data failure. In particular, to solve problems from the perspective of data, this study defines data integrity and data consistency for use in identifying data failure. This study, by identifying the exact type of failure through analysis of the cause of failure, proposes criteria for performing relevant recovery. In addition, the experiments have been made to suggest the duration as to how long the data should be stored in the gateway when such a data failure occurs.

• Earthquakes and Structures
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• v.14 no.5
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• pp.425-436
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• 2018

The design of seismically isolated structures considering the stochastic nature of excitations, base isolators' design parameters, and superstructure properties requires robust reliability analysis methods to calculate the failure probability of the entire system. Here, by applying artificial neural networks, we proposed a robust technique to accelerate the estimation of failure probability of equipped isolated structures. A three-story isolated building with susceptible facilities is considered as the analytical model to evaluate our technique. First, we employed a sensitivity analysis method to identify the critical sources of uncertainty. Next, we calculated the probability of failure for a particular set of random variables, performing Monte Carlo simulations based on the dynamic nonlinear time-history analysis. Finally, using a set of designed neural networks as a surrogate model for the structural analysis, we assessed once again the probability of the failure. Comparing the obtained results demonstrates that the surrogate model can attain precise estimations of the probability of failure. Moreover, our proposed approach significantly increases the computational efficiency corresponding to the dynamic time-history analysis of the structure.

• Journal of Korean Society of Water and Wastewater
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• v.23 no.3
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• pp.295-303
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• 2009

In the present study, a reliability analysis calculating the probability of system failure has been performed using cut set and results of numerical analysis for unsteady flow in pipe. Especially, the probability of system failure has been evaluated regarding the effect of valve closure which is a really important activity in operation of piping system. In spite of small amount of demand, it was found that fast valve closure can generate high probability of system failure. Furthermore, it was confirmed that surge tank can reduce the unsteady effects and probability of system failure in water distribution system. From the results, it was found that the unsteady flow has a significant effect on the probability of system failure Furthermore, it was able to find which pipe or cut set has high probability of system failure. So it could be used to determine which pipe or cut set has a priority of repair and replacement. Therefore, reliability analysis regarding unsteady flow has to be performed for the planning, designing, maintenance, and operation of piping system.