• Geomechanics and Engineering
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• v.27 no.6
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• pp.605-614
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• 2021

Water inrush from fault is one of the most severe hazards during tunnel excavation. However, the traditional evaluation methods are deficient in both quantitative evaluation and uncertainty handling. In this paper, a comprehensive methodology method combined intuitionistic fuzzy AHP with a Bayesian network for the risk assessment of water inrush from fault in the subsea tunnel was proposed. Through the intuitionistic fuzzy analytic hierarchy process to replace the traditional expert scoring method to determine the prior probability of the node in the Bayesian network. After the field data is normalized, it is classified according to the data range. Then, using obtained results into the Bayesian network, conduct a risk assessment with field data which have processed of water inrush disaster on the tunnel. Simultaneously, a sensitivity analysis technique was utilized to investigate each factor's contribution rate to determine the most critical factor affecting tunnel water inrush risk. Taking Qingdao Kiaochow Bay Tunnel as an example, by predictive analysis of fifteen fault zones, thirteen of them are consistent with the actual situation which shows that the IFAHP-Bayesian Network method is feasible and applicable. Through sensitivity analysis, it is shown that the Fissure development and Apparent resistivity are more critical comparing than other factor especially the Permeability coefficient and Fault dip. The method can provide planners and engineers with adequate decision-making support, which is vital to prevent and control tunnel water inrush.

• The Journal of Information Systems
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• v.21 no.1
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• pp.1-17
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• 2012

Common Method Bias(CMB) may cause the potential inflation of correlations between measures assessed via the same method. The problem of CMB has been well known in behavioral sciences because the survey method with self-reporting is vulnerable to CMB. Thus, the discussion on CMB is still ongoing in the MIS research in US. However, in Korea, the MIS research has never paid attention on the CMB problem. The purpose of this study is to examine the CMB problem in the Korean MIS research. To evaluate the effect of CMB, empirical studies on Technology Acceptance Model(TAM) are selected because (1) TAM is one of the MIS research areas studied intensively, (2) TAM is a theoretical model well supported by the existing empirical studies so that the result of this study would have a great ripple effect when the CMB problem turned out to be serious, (3) CMB is domain-specific. 47 TAM samples (out of 45 studies) from three Korean Journals were selected and the relevant data were collected such as correlation matrixes and the measures of the dependent variable. To find and evaluate the size of CMB, two analytic methods (Marker-Variable Technique and Method-Method Pair Technique) are employed. The result showed that there exists CMB in the Korean studies but the problem is not so serious to distort the empirical testing, compared with that of US studies. However, considering that CMB can contaminate the testing results, Korean MIS researchers should explicitly deal with the problem in designing empirical studies and collecting data.

• Journal of the Korea Society for Simulation
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• v.14 no.4
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• pp.19-30
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• 2005

Due to explosive expansion in R & D efforts for advancement of technological predominance by Enterprises, the volume of technical information rapidly increases and emphasize on the valuation of this information has grown ever increasingly important. Therefore the requirement for systematic management and safeguard and accumulation of these intellectual properties of the Enterprise is in very high demand. A lot of effort and research has been carried out and many on going studies in progress to try to derive the optimum solution on how to manage information retention policy, processes, execution method, and hardware to execute the information with and etc. The intent of this thesis is to recommend a way for the Enterprise on how to evaluate the valuation of the data and to suggest the method on how to manage these intellectual properties by way of using Information Lifecycle Management theory which manages data according to the business valuation of the data. The decision on valuation of data and retention cycle is based on analytic method of a nonparametric regression, experimentation was carried out by applying to Enterprise Document Management System to present the suitable retention cycle according to the valuation and variety of attribute of data.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.11
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• pp.3619-3637
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• 2022

Big data analytics offers endless opportunities for operational enhancement by extracting valuable insights from complex voluminous data. Hadoop is a comprehensive technological suite which offers solutions for the large scale storage and computing needs of Big data. The performance of Hadoop is closely tied with its configuration settings which depends on the cluster capacity and the application profile. Since Hadoop has over 190 configuration parameters, tuning them to gain optimal application performance is a daunting challenge. Our approach is to extract a subset of impactful parameters from which the performance enhancing sub-optimal configuration is then narrowed down. This paper presents a statistical model to analyze the significance of the effect of Hadoop parameters on a variety of performance metrics. Our model decomposes the total observed performance variation and ascribes them to the main parameters, their interaction effects and noise factors. The method clearly segregates impactful parameters from the rest. The configuration setting determined by our methodology has reduced the Job completion time by 22%, resource utilization in terms of memory and CPU by 15% and 12% respectively, the number of killed Maps by 50% and Disk spillage by 23%. The proposed technique can be leveraged to ease the configuration tuning task of any Hadoop cluster despite the differences in the underlying infrastructure and the application running on it.

• Journal of Internet Computing and Services
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• v.23 no.5
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• pp.135-143
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• 2022

As the world has implemented social distancing and telecommuting due to the spread of COVID-19, real-time streaming sessions based on routing protocols have increased dependence on the Internet due to the activation of video and voice-related content services and cloud computing. BGP is the most widely used routing protocol, and although many studies continue to improve security, there is a lack of visual analysis to determine the real-time nature of analysis and the mis-detection of algorithms. In this paper, we analyze BGP data, which are powdered as normal and abnormal, on a real-world basis, using an anomaly detection algorithm that combines statistical and post-processing statistical techniques with Rule-based techniques. In addition, we present an interactive spatio-temporal analysis plan as an intuitive visualization plan and analysis result of the algorithm with a map and Sankey Chart-based visualization technique.

• Geophysics and Geophysical Exploration
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• v.19 no.1
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• pp.45-50
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• 2016

Generally, a point source has been routinely used in the electrical resistivity measurements because of easy installation. If steel-cased wells are used as long electrodes, we can expect the better depth of investigation. However, the resistivity data with long electrodes can not be processed with a conventional inversion algorithm because a long electrode produces the different primary potential distribution compared with the point source. In this study, we proposed a new technique to process the electrical resistivity data with long electrodes by replacing the long electrode with a sequence of point electrodes. Comparing the potentials obtained from the technique with the analytic/numerical solution, we ensure that the proposed technique can be used for the numerical resistivity modeling based on the finite difference or finite element method.

• Transactions of the Korean Society of Mechanical Engineers
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• v.11 no.1
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• pp.110-117
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• 1987

A new kinematically admissible velocity field for a generalized three-dimensional flow is introduced, in which the flow is bounded by an analytic die-profile function. Then, by applying the upper-bound method th the velocity field, the flow patterns as the upper-bound method are obtained. Extrusion of elliptic sections from round billets is chosen as a computational example. Computation and experiments are carried out for work-hardening material such as aluminum alloy 2024. In order to visualize the plastic flow, the grid marking technique is employed. The theoretical predictions both in extrusion load and deformed pattern are in good agreement with the experimental data.

• IEMEK Journal of Embedded Systems and Applications
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• v.13 no.4
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• pp.205-214
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• 2018

The reliability test is a crucial step for ensuring robustness of high-cost and complex weapon systems. In this paper, we present a set of quantitative criteria to select critical parts or components in weapon systems for the reliability test, and implement a fuzzy inference system by applying developed criteria to fuzzy theory. We classify the selection criteria of critical parts or components into four fuzzy sets and membership functions. A fuzzy inference rule is proposed based on the AHP (Analytic Hierarchy Process) analysis technique so as to derive a convincing reliability test. The credibility of the fuzzy inference system is confirmed through a case study using actual equipment data exacted from an existent weapon system.

• Communications for Statistical Applications and Methods
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• v.9 no.1
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• pp.63-73
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• 2002

The one of analytic imputation technique involving conditional means was mentioned by Schafer and Schenker(2000). And their derivations are based on asymptotic expansions of point estimator and their associated variance estimator, and the result of imputation can be thought of as first-order approximations to the estimators. Specially in this paper, we are presenting the method of estimating a Binomial proportion with Bayesian approach of imputed conditional means. That is, instead of using maximum likelihood(ML) estimator to estimate a Binomial proportion, in general, we use the Bayesian estimators and will show the result of estimated Imputed conditional means.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.15 no.9 s.102
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• pp.1108-1117
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• 2005

A robust damage detection method using short-time Fourier transform and beating phenomena is presented as an estimating tool of the healthiness of large structures. The present technique makes use of beating phenomena that manifest themselves when two signals of similar frequencies are added or subtracted. Unlike most existing methods based on vibration signals, the present approach does not require an analytic model for target structures. Furthermore, the main advantage of the proposed method compared to the competing diagnostic method using vibration data is its robustness. The proposed method is not affected by the amplitude of exciting signals and the location of exciting points. From a measuring view point. the location of sensing point have no influence on the performance of the present method. With a view to verifying the effectiveness of this method. a series of experiments are made and the results show its possibility as a robust damage diagnostic method.