• Journal of Information Technology Services
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• v.17 no.1
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• pp.91-103
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• 2018

This study developed a prediction model using machine learning technology and predicted the success of health consulting by using life log data generated through u-Health service. The model index of the Random Forest model was the highest using. As a result of analyzing the Random Forest model, blood pressure was the most influential factor in the success or failure of metabolic syndrome in the subjects of u-Health service, followed by triglycerides, body weight, blood sugar, high cholesterol, and medication appear. muscular, basal metabolic rate and high-density lipoprotein cholesterol were increased; waist circumference, Blood sugar and triglyceride were decreased. Further, biometrics and health behavior improved. After nine months of u-health services, the number of subjects with four or more factors for metabolic syndrome decreased by 28.6%; 3.7% of regular drinkers stopped drinking; 23.2% of subjects who rarely exercised began to exercise twice a week or more; and 20.0% of smokers stopped smoking. If the predictive model developed in this study is linked with CBR, it can be used as case study data of CBR with high probability of success in the prediction model to improve the compliance of the subject and to improve the qualitative effect of counseling for the improvement of the metabolic syndrome.

• Journal of the Society of Naval Architects of Korea
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• v.52 no.1
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• pp.88-95
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• 2015

For the frequency-domain spectral fatigue analysis, the probability density function of stress range needs to be estimated based on the stress spectrum only, which is a frequency domain representation of the response. The probability distribution of the stress range of the narrow-band spectrum is known to follow the Rayleigh distribution, however the PDF of wide-band spectrum is difficult to define with clarity due to the complicated fluctuation pattern of spectrum. In this paper, efforts have been made to figure out the links between the probability density function of stress range to the structural response of wide-band Gaussian random process. An artificial neural network scheme, known as one of the most powerful system identification methods, was used to identify the multivariate functional relationship between the idealized wide-band spectrums and resulting probability density functions. To achieve this, the spectrums were idealized as a superposition of two triangles with arbitrary location, height and width, targeting to comprise wide-band spectrum, and the probability density functions were represented by the linear combination of equally spaced Gaussian basis functions. To train the network under supervision, varieties of different wide-band spectrums were assumed and the converged probability density function of the stress range was derived using the rainflow counting method and all these data sets were fed into the three layer perceptron model. This nonlinear least square problem was solved using Levenberg-Marquardt algorithm with regularization term included. It was proven that the network trained using the given data set could reproduce the probability density function of arbitrary wide-band spectrum of two triangles with great success.

• The Bulletin of The Korean Astronomical Society
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• v.40 no.1
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• pp.84.2-84.2
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• 2015

There are probabilistic forecast models for solar flare occurrence, which can be evaluated by various skill scores (e.g. accuracy, critical success index, heidek skill score, true skill score). Since these skill scores assume that two types of forecast errors (i.e. false alarm and miss) are equal or constant, which does not take into account different situations of users, they may be unrealistic. In this study, we make an evaluation of a probabilistic flare forecast model (Lee et al. 2012) which use sunspot groups and its area changes as a proxy of flux emergence. We calculate daily solar flare probabilities from 1996 to 2014 using this model. Overall frequencies are 61.08% (C), 22.83% (M), and 5.44% (X). The maximum probabilities computed by the model are 99.9% (C), 89.39% (M), and 25.45% (X), respectively. The skill scores are computed through contingency tables as a function of forecast probability, which corresponds to the maximum skill score depending on flare class and type of a skill score. For the critical success index widely used, the probability threshold values for contingency tables are 25% (C), 20% (M), and 4% (X). We use a value score with cost/loss ratio, relative importance between the two types of forecast errors. We find that the forecast model has an effective range of cost/loss ratio for each class flare: 0.15-0.83(C), 0.11-0.51(M), and 0.04-0.17(X), also depending on a lifetime of satellite. We expect that this study would provide a guideline to determine the probability threshold for space weather forecast.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.9
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• pp.2370-2387
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• 2012

A new security management model based on Rough set and Bayesian learner is proposed in the paper. The model focuses on finding out malicious nodes and getting them under control. The degree of dissatisfaction (DoD) is defined as the probability that a node belongs to the malicious node set. Based on transaction history records local DoD (LDoD) is calculated. And recommended DoD (RDoD) is calculated based on feedbacks on recommendations (FBRs). According to the DoD, nodes are classified and controlled. In order to improve computation accuracy and efficiency of the probability, we employ Rough set combined with Bayesian learner. For the reason that in some cases, the corresponding probability result can be determined according to only one or two attribute values, the Rough set module is used; And in other cases, the probability is computed by Bayesian learner. Compared with the existing trust model, the simulation results demonstrate that the model can obtain higher examination rate of malicious nodes and achieve the higher transaction success rate.

• International Journal of Computer Science & Network Security
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• v.22 no.11
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• pp.19-24
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• 2022

The article determines that, in the preservation of cultural heritage, lifestyle, an important role is played by the subjects' high assessment of the probability of achieving the result they need through the implementation of traditional models, ways of interaction. If dissatisfaction with the results of interaction is great, but there are no necessary conditions for a phased resolution of contradictions, for changing, developing interpersonal relations within the framework of the existing system, interaction becomes more difficult. It has been determined that the presence of effective models that show the possibility of meeting the requirements for the psyche of a variety of individuals from the side of activity, activating an extended search for mutually acceptable ways to success, depends on the development of the personality and its social relations, the success of interaction between people, socially psychological climate in the team.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.17 no.32
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• pp.227-232
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• 1994

In the performance domain, physical performance is a measure that represents some degree of system, subsystem, component or device success in a continuous sense, as opposed to a classical binomial sense (success or failure). If applicable sensing and monitoring means exist, physical performance can be observed over time, along with explanatory variables or covariables. Performance-based reliability represents the probability that performance will remain satisfactory over a finite period of time or usage cycles in the future when a performance critical limit (which represents an appropriate definition of failure in terms of performance) is set at a fixed level, based on application requirements. In the case of inadequate knowledge of the failure mechanics, this physical based empirical modeling concept along with performance degradation knowledge can serve as an important analysis tool in reliability work in product and process improvement.

• Journal of the Korea Institute of Military Science and Technology
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• v.16 no.6
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• pp.819-827
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• 2013

Compared to legacy frequency hopping communications, future radio communications are required the secure and high data rate, ad-hoc network communication. In this paper, we have designed the network communication structure on the frequency hopping mode, and analyzed the performance of synchronization on the frequency hopping network radio systems. The design results are shown the initial sync. phase of approximately 9 hops and the traffic packet phase of approximately 30 hops. Also, we have simulated the performance on the communication conditions which are carrier bandwidth of 50kHz, user data rate of 64kbps and OQPSK modulation scheme in AWGN. In the simulation, we analyzed the correlation and the performance of synchronization success. The result of simulation show 99% probability for synchronization success at $E_b/N_o$ -4dB.

• Proceedings of the Korean Society for Quality Management Conference
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• 2009.10a
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• pp.234-240
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• 2009

The growing mobile products market is expected energy efficiency. So product design is more important focusing on reducing power consumption than improving technology of color sense. A Organic light emission diode is in limelight of the best display to satisfy market expectation. A Organic light emission diode is achieved low power consumption, pixel response which was fast for its time, high contrast of brightness and wide color reproduction raio. Therefore there is a fierce competition for the organic light emission diode development between a country and another country over business. The technical value's life is short because of a fierce development competition, and there is little probability that technical success become business success. In this study, the purpose is reduce the time for life test by accelerated current and it can do production possible design by accelerated life model in design phase.

• International journal of advanced smart convergence
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• v.12 no.3
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• pp.13-18
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• 2023

This paper aims to investigate data features for neighbor path selection (NPS) in computer network with regional failures. It is necessary to find an available alternate communication path in advance when regional failures due to earthquakes or forest fires occur simultaneously. We describe previous general heuristics and simulation heuristic to solve the NPS problem in the regional fault network. The data features of general heuristics using proximity and sharing factor and the data features of simulation heuristic using machine learning are explained through examples. Simulation heuristic may be better than general heuristics in terms of communication success. However, additional data features are necessary in order to apply the simulation heuristic to the real environment. We propose novel data features for NPS in computer network with regional failures and Keras modeling for computing the communication success probability of candidate neighbor path.

• Nuclear Engineering and Technology
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• v.54 no.12
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• pp.4601-4619
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• 2022

The classical Probabilistic Safety Analysis (PSA) does not include any time dependence explicitly. However, the success criteria (SC) could evolve during the cycle for some initiating events. In that sense, there is a type of sequence in which this time-dependency is quite important, the family of Anticipated Transient without Scram (ATWS) sequences in Pressurized Water Reactors. Therefore, a new risk-informed approach is proposed in this paper, which makes it possible to obtain the time-dependent SC evolution of the safety functions affected by the Moderator Temperature Coefficient (MTC) value. Then, the evolution of the ATWS conditional core damage probability (CCDP) could be obtained using a PSA model. To quantify the CCDP, the average values of the time-dependent failure probabilities must be computed. Finally, the comparison between the CCDP obtained through the application of the classical PSA approach and the new one makes it possible to quantify the impact of time-dependence on the SC of the headers that this new risk-informed ATWS approach can provide.