• Wind and Structures
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• v.15 no.3
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• pp.209-221
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• 2012

The flutter reliability analysis of long span bridges requires use of a software tool that predicts the uncertainty in a flutter response due to uncertainties in the model formulation and input parameters. Existing flutter analysis numerical codes are not capable of dealing with stochastic uncertainty in the analysis of long span bridges. The goal of the present work is to develop a software tool (FREASB) to enable designers to efficiently and accurately conduct flutter reliability analysis of long span bridges. The FREASB interfaces an open-source Matlab toolbox for structural reliability analysis (FERUM) with a typical deterministic flutter analysis code. The paper presents a brief introduction to the generalized first-order reliability method implemented in FREASB and key steps involved in coupling it with a typical deterministic flutter analysis code. A numerical example concerning flutter reliability analysis of a long span suspension bridge with a main span of 1385 m is presented to demonstrate the application and effectiveness of the methodology and the software.

• Korean Journal of Biological Psychiatry
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• v.12 no.2
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• pp.165-172
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• 2005

Objectives:The purpose of this study is to 1) conduct a discrimination analysis of schizophrenia and bipolar affective disorder using MMPI profile through artificial neural network analysis and logistic regression analysis, 2) to make a comparison between advantages and disadvantages of the two methods, and 3) to demonstrate the usefulness of artificial neural network analysis of psychiatric data. Procedure:The MMPI profiles for 181 schizophrenia and bipolar affective disorder patients were selected. Of these profiles, 50 were randomly placed in the learning group and the remaining 131 were placed in the validation group. The artificial neural network was trained using the profiles of the learning group and the 131 profiles of the validation group were analyzed. A logistic regression analysis was then conducted in a similar manner. The results of the two analyses were compared and contrasted using sensitivity, specificity, ROC curves, and kappa index. Results:Logistic regression analysis and artificial neural network analysis both exhibited satisfactory discriminating ability at Kappa index of greater than 0.4. The comparison of the two methods revealed artificial neural network analysis is superior to logistic regression analysis in its discriminating capacity, displaying higher values of Kappa index, specificity, and AUC(Area Under the Curve) of ROC curve than those of logistic regression analysis. Conclusion:Artificial neural network analysis is a new tool whose frequency of use has been increasing for its superiority in nonlinear applications. However, it does possess insufficiencies such as difficulties in understanding the relationship between dependent and independent variables. Nevertheless, when used in conjunction with other analysis tools which supplement it, such as the logistic regression analysis, it may serve as a powerful tool for psychiatric data analysis.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.12
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• pp.553-564
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• 2014

In this paper, we propose the system for automatic generation of issue analysis report based on social big data mining, with the purpose of resolving three problems of the previous technologies in a social media analysis and analytic report generation. Three problems are the isolation of analysis, the subjectivity of experts and the closure of information attributable to a high price. The system is comprised of the natural language query analysis, the issue analysis, the social big data analysis, the social big data correlation analysis and the automatic report generation. For the evaluation of report usefulness, we used a Likert scale and made two experts of big data analysis evaluate. The result shows that the quality of report is comparatively useful and reliable. Because of a low price of the report generation, the correlation analysis of social big data and the objectivity of social big data analysis, the proposed system will lead us to the popularization of social big data analysis.

• Proceedings of the Korean Geotechical Society Conference
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• 2005.03a
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• pp.179-184
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• 2005

Shear strength parameters obtained from filed survey are important factors in the analysis of slope stability. In this study, sensitivity analysis was performed to evaluate the effect of input parameters on the analysis of slope stability. The input parameters selected for sensitivity analysis were slope angle, cohesion, and friction angle. Monte-Carlo Simulation method was used for calculating input parameters and the factor of safety was computed by means of limit equilibrium method. A rock slope, which has failed in the field, was used for the sensitivity analysis in the analysis of slope stability. The result of analysis shows that the factor of safety of the rock slope was a little low. From partial correlation coefficient(PPC) of input parameters determined from the sensitivity analysis, slope stability was dependant on cohesion and slope angle. The effect of friction angle was lower than that of cohesion and slope angle on slope stability.

• Journal of Drive and Control
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• v.16 no.1
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• pp.36-44
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• 2019

Variable displacement swash plate piston pump analysis requires electric, hydraulics and dynamics which are similar to the one's incorporated in the complex fluid power and mechanical systems. The main variable capacity for the swash plate piston pumps, hydraulics or simple kinematic (swash plate degree, piston displacement) models are analyzed using AMESim, a multi-physics analysis program. AMESim is a multi-physics hydraulic analysis program that is considered good for the environment but not appropriate for environmental analysis for multibody dynamics. In this study, the analytical model of the swash plate type hydraulic piston pump variable capacity is modeled by combining the hydraulic part and the dynamic part through co-simulation of multibody dynamics program (Virtual.lab Motion) and multi-physics analysis (AMESim). This paper describes the whole modeling analysis method on the mechanical analysis of the multi-body dynamics program and how the hydraulic analysis in multi-physics analysis program works. This paper also presents a methodology for analyzing complex fluid power systems.

• KOREAN JOURNAL OF PACKAGING SCIENCE & TECHNOLOGY
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• v.8 no.2
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• pp.18-26
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• 2002

Films of methylcellulose(MC), chitosan and their blends were prepared using water and acid solution as a solvent. The transition behavior and miscibility of polymers and their blends were characterized by dynamic mechanical analysis(DMA) and thermogravimetric analysis(TGA). The DMA analysis of PEG400/MC blends has shown that PEG400 was compatible with MC and was effective plasticizer since the curves of $tan{\delta}$ against temperature exhibited single peak, corresponding to single glass transition temperature, which were displaced to lower values with increasing PEG400 content. Results of DMA analysis and TGA analysis of MC/chitosan blends indicate that there are some miscibility between MC and chitosan in the blends, attributed to the similarities between two polysaccharides and interactions of two polymers in the blends. The inclusion of PEG400 in the blends increase the miscibility between two components in the blends.

• Journal of Information Processing Systems
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• v.15 no.3
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• pp.500-519
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• 2019

The blooming of social media has simulated interest in sentiment analysis. Sentiment analysis aims to determine from a specific piece of content the overall attitude of its author in relation to a specific item, product, brand, or service. In sentiment analysis, the focus is on the subjective sentences. Hence, in order to discover and extract the subjective information from a given text, researchers have applied various methods in computational linguistics, natural language processing, and text analysis. The aim of this paper is to provide an in-depth up-to-date study of the sentiment analysis algorithms in order to familiarize with other works done in the subject. The paper focuses on the main tasks and applications of sentiment analysis. State-of-the-art algorithms, methodologies and techniques have been categorized and summarized to facilitate future research in this field.

• Nuclear Engineering and Technology
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• v.31 no.6
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• pp.8-22
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• 1999

This study was performed to comparatively evaluate selected Human Reliability Analysis (HRA) methods which mainly focus on cognitive error analysis, and to derive the requirement of a new human error analysis (HEA) framework for Accident Management (AM) in Nuclear Power Plants (NPPs). In order to achieve this goal, we carried out a case study of human error analysis on an AM task in NPPs. In the study we evaluated three cognitive HEA methods, HRMS, CREAM and PHECA, which were selected through the review of the currently available seven cognitive HEA methods. The task of reactor cavity flooding was chosen for the application study as one of typical tasks of AM in NPPs. From the study, we derived seven requirement items for a new HEA method of AM in NPPs. We could also evaluate the applicability of three cognitive HEA methods to AM tasks. CREAM is considered to be more appropriate than others for the analysis of AM tasks, HRMS is also applicable to the error analysis of AM tasks. But, PHECA is regarded less appropriate for the predictive HEA technique as well as for the analysis of AM tasks. In addition to these, the advantages and disadvantagesofeachmethodaredescribed.

• Ocean Systems Engineering
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• v.9 no.3
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• pp.261-285
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• 2019

Nowadays in offshore industry there are emerging hazards with vague property such as act of terrorism, act of war, unforeseen natural disasters such as tsunami, etc. Therefore industry professionals such as offshore energy insurers, safety engineers and risk managers in order to determine the failure rates and frequencies for the potential hazards where there is no data available, they need to use an appropriate method to overcome this difficulty. Furthermore in conventional risk based analysis models such as when using a fault tree analysis, hazards with vague properties are normally waived and ignored. In other word in previous situations only a traditional probability based fault tree analysis could be implemented. To overcome this shortcoming fuzzy set theory is applied to fault tree analysis to combine the known and unknown data in which the pre-combined result will be determined under a fuzzy environment. This has been fulfilled by integration of a generic bow-tie based risk analysis model into the risk assessment phase of the Risk Management (RM) cycles as a backbone of the phase. For this reason Fault Tree Analysis (FTA) and Event Tree Analysis (ETA) are used to analyse one of the significant risk factors associated in offshore terminals. This process will eventually help the insurers and risk managers in marine and offshore industries to investigate the potential hazards more in detail if there is vagueness. For this purpose a case study of offshore terminal while coinciding with the nature of the Caspian Sea was decided to be examined.

• Journal of Korean Tunnelling and Underground Space Association
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• v.3 no.4
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• pp.3-15
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• 2001

Generally, it has been noted that underground structures have a consistent record of suffering much less damage than surface facilities during earthquakes; but it is still necessary to illustrate the dynamic response of tunnel structures subject to earthquake loadings and to provide the appropriate method for the seismic analysis of underground tunnel structures since many types of underground structures have been and will be constructed in countries situated within seismic zones. In this study, first, seismic analyses for underground tunnel structures are performed by using quasistatic analysis method and dynamic analysis method. Second, seismic analyses in tunnel portals are performed by using above methods. The results of seismic analyses for the tunnel structure show that the tunnel structure conforms to ground deformation and that seismic design by using the quasi-static analysis method is more conservative than that by using the dynamic analysis. The results of the dynamic FEM analysis for the tunnel structure show that the simplified 2-D FEM analysis using a sine wave rather than the 3-D FEM analysis can be adopted for seismic analysis. Finally, the results of the dynamic FEM analysis in tunnel portals show that the force acting on the lining is largest near to the tunnel portal when an earthquake wave propagates parallel to tunnel axis.