• Journal of Mechanical Science and Technology
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• v.18 no.6
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• pp.946-954
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• 2004

A model in the form of a Bearing Load Distribution (BLD) matrix in the Multi Bearing Rotor System (MBRS) is established by a transfer matrix equation with the consideration of a bearing load, elevation and uniform load distribution. The concept of Bearing Load Sensitivity (BLS) is proposed and matrices for load and elevation sensitivity are obtained. In order to share MBRS design resources on the Internet with remote customers, the basic principle of Remote Computing (RC) based on the Internet is introduced ; the RC of the BLD and BLS is achieved by Microsoft Active Server Pages (ASP) technology.

• Transactions of the Korean Society of Automotive Engineers
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• v.7 no.7
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• pp.94-103
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• 1999

A model for the prediction of combustion and exhaust emissions of DI diesel engine has been formulated and developed . This model is a quasi-dimensional phenomenological one and is based on multi-zone combustion modelling concept. It takes into consideration, on a zonal basis ,detailed of fuel spray formation, droplet evaporation, air-fuel mixing, spray wall interaction, swirl , heat transfer, self ignition and burning rate . The emission model is considered with chemical equipment , as well as the kinetics of fuel. NO and soot reactions in order to calculate the pollutant concentrations within each zone and the whole of cylinder . The accuracy of prediction versus experimental data and the capability of the model in predicting engine heat release, cylinder pressure and all the major exhaust emissions on zonal and cumulative basis., is demonstrated. Detailed prediction results showing the sensitivity of the model bv various injection rates are presented and discussed.

• The Journal of Korean Medicine
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• v.29 no.1
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• pp.7-14
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• 2008

Purpose : The purpose of study was to develop generalized validity evaluation methods and terms for Sasang type diagnostic tests. Methods : A generalized statistical evaluation model for Sasang typology was suggested and generalized validity evaluation indices were proposed with this model. Results : The usefulness of validity evaluations, such as sensitivity and specificity values, were confirmed by the systematic review of the data from previously reported studies. Conclusion :Major obstacles in the multi-facet analysis and systematic review for Sasang type diagnostic tests were discussed with this test validity study.

• Advances in aircraft and spacecraft science
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• v.4 no.2
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• pp.185-202
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• 2017

In a flexible airvehicle, an assessment of the structural coupling levels through analysis and experiments provides structural data for the design of notch filters which are generally utilized in the flight control system to attenuate the flexible response pickup. This is necessitated as during flight, closed loop control actuation driven with flexible response inputs could lead to stability and performance related problems. In the present work, critical parameters influencing servoelastic response have been identified. A sensitivity study has been carried out to assess the extent of influence of each parameter. A multi-parameter tuning approach has been implemented to achieve an enhanced analytical model for improved predictions of aircraft servoelastic response. To illustrate the model updation approach, initial and improved test analysis correlation of lateral servoelastic responses for a generic flexible airvehicle are presented.

• Geophysics and Geophysical Exploration
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• v.5 no.2
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• pp.78-83
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• 2002

The finite element method combined with the sensitivity method is adopted for 2-dimensionl Fourier transform inversion. To improve the efficiency of inversion calculation, multi-resolution wavelet method is proposed., Theoretical data which is obtained from above method is shown to examine the proposed method. Theoretical model assumes that underground cavity is located in limestone area. In theoretical model, 16 current and potential electrodes are located to get theoretical data. It is shown that the about inversion method is very exact and useful calculation method, in case the larger model is very small such as under ground cavity.

• Nuclear Engineering and Technology
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• v.51 no.4
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• pp.968-976
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• 2019

This paper presents a number of verification case studies for a recently developed sensitivity/uncertainty code package. The code package, ROMUSE (Reduced Order Modeling based Uncertainty/Sensitivity Estimator) is an effort to provide an analysis tool to be used in conjunction with reactor core simulators, in particular the Virtual Environment for Reactor Applications (VERA) core simulator. ROMUSE has been written in C++ and is currently capable of performing various types of parameter perturbations and associated sensitivity analysis, uncertainty quantification, surrogate model construction and subspace analysis. The current version 2.0 has the capability to interface with the Design Analysis Kit for Optimization and Terascale Applications (DAKOTA) code, which gives ROMUSE access to the various algorithms implemented within DAKOTA, most importantly model calibration. The verification study is performed via two basic problems and two reactor physics models. The first problem is used to verify the ROMUSE single physics gradient-based range finding algorithm capability using an abstract quadratic model. The second problem is the Brusselator problem, which is a coupled problem representative of multi-physics problems. This problem is used to test the capability of constructing surrogates via ROMUSE-DAKOTA. Finally, light water reactor pin cell and sodium-cooled fast reactor fuel assembly problems are simulated via SCALE 6.1 to test ROMUSE capability for uncertainty quantification and sensitivity analysis purposes.

• Journal of Korean Society for Quality Management
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• v.18 no.1
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• pp.65-76
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• 1990

A lot-sizing model for multi-stage MRP systems is proposed, in which known demands must be satisfied. In this model, an approach with considerations of initial inventory and limited production capacity is involved. Most of the studies on the lot-sizing techniques for multi-stage material requirement planning systems have been focused upon two basic approaches. One approach is to develope an algorithm yielding an optimal solution. Due to the computational complexity and sensitivity of the optimal solution to the problem of lot sizing, heuristic approaches are often employed. In this paper, the heuristic approach is used by sequential application of a single-stage algorithm with a set of modified cost by the concept of multi-echelon costs. The proposed method is compared with an lot-sizing method(Florian-Klein Model) to prove its effectiveness by numerical examples.

• Journal of the Korean Society for Nondestructive Testing
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• v.30 no.6
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• pp.527-538
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• 2010

This paper presents a nondestructive evaluation approach for system identification (SID) of real railway bridges using field vibration test results. First, a multi-phase SID scheme designed on the basis of eigenvalue sensitivity concept is presented. Next, the proposed multi-phase approach is evaluated from field vibration tests on a real railway bridge (Wondongcheon bridge) located in Yangsan, Korea. On the steel girder bridge, a few natural frequencies and mode shapes are experimentally measured under the ambient vibration condition. The corresponding modal parameters are numerically calculated from a three-dimensional finite element (FE) model established for the target bridge. Eigenvalue sensitivities are analyzed for potential model-updating parameters of the FE model. Then, structural subsystems are identified phase-by-phase using the proposed model-updating procedure. Based on model-updating results, a baseline model and a nondestructive evaluation of test bridge are identified.

• Journal of Environmental Impact Assessment
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• v.12 no.4
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• pp.271-279
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• 2003

Temperature and humidity forecasting have been performed using artificial neural networks model(ANN). We composed ANN with multi-layer perceptron which is 2 input layers, 2 hidden layers and 1 output layer. Back propagation algorithm was used to train the ANN. 6 nodes and 12 nodes in the middle layers were appropriate to the temperature model for training. And 9 nodes and 6 nodes were also appropriate to the humidity model respectively. 90% of the all data was used learning set, and the extra 10% was used to model verification. In the case of temperature, average temperature before 15 minute and humidity at present constituted input layer, and temperature at present constituted out-layer and humidity model was vice versa. The sensitivity analysis revealed that previous value data contributed to forecasting target value than the other variable. Temperature was pseudo-linearly related to the previous 15 minute average value. We confirmed that ANN with multi-layer perceptron could support pollutant dispersion model by computing meterological data at real time.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.2
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• pp.632-657
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• 2022

Detecting web attacks is a major challenge, and it is observed that the use of simple models leads to low sensitivity or high false positive problems. In this study, we aim to develop a robust two-stage deep learning based stacked ensemble web application firewall. Normal and abnormal classification is carried out in the first stage of the proposed WAF model. The classification process of the types of abnormal traffics is postponed to the second stage and carried out using an integrated stacked ensemble model. By this way, clients' requests can be served without time delay, and attack types can be detected with high sensitivity. In addition to the high accuracy of the proposed model, by using the statistical similarity and diversity analyses in the study, high generalization for the ensemble model is achieved. Within the study, a comprehensive, up-to-date, and robust multi-class web anomaly dataset named GAZI-HTTP is created in accordance with the real-world situations. The performance of the proposed WAF model is compared to state-of-the-art deep learning models and previous studies using the benchmark dataset. The proposed two-stage model achieved multi-class detection rates of 97.43% and 94.77% for GAZI-HTTP and ECML-PKDD, respectively.