• International Journal of Heart Failure
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• v.6 no.3
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• pp.93-106
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• 2024

Being commonly diagnosed in elderly women and associated with comorbidities as well as ageing-related cardio-vascular changes, heart failure with preserved ejection fraction (HFpEF) has been recently considered as a distinct cardiogeriatric syndrome. Frailty is another frequent geriatric syndrome. HFpEF and frailty share common underlying mechanisms, often co-exist, and represent each other's risk factors. A threshold of 65 years old is usually used to screen patients for both frailty and HFpEF in research and clinical settings. However, both HFpEF and frailty are very heterogenous conditions that may develop at younger ages. In this review we aim to provide a broader overview on the coexistence of HFpEF and frailty throughout the lifetime. We hypothesize that HFpEF and frailty patients' profiles (young, elderly, superaged) represent a continuum of the common ageing process modified by cumulative exposure to risk factors resulting to a presentation of HFpEF and frailty at different ages. We believe, that suggested approach might stimulate assessment of frailty in HFpEF assessment and vice versa regardless of age and early implementation of targeted interventions. Future studies of pathophysiology, clinical features, and outcomes of frailty in HFpEF by age are needed.

• Structural Engineering and Mechanics
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• v.38 no.4
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• pp.479-501
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• 2011

Even though fiber reinforced polymer (FRP) has been widely used as a retrofitting material, the FRP behavior and effect in FRP retrofitted structure under blast loading, impulsive loading with instantaneous time duration, has not been accurately examined. The past studies have focused on the performance of FRP retrofitted structures by making simplifications in modeling, without incorporating accurate failure mechanisms of FRP. Therefore, it is critical to establish an analytical model that can properly consider the specific features of FRP material in evaluating the response of retrofitted concrete structures under blast loading. In this study, debonding failure analysis technique for FRP retrofitted concrete structure under blast loading is suggested by considering FRP material characteristics and debonding failure mechanisms as well as rate dependent failure mechanism based on a blast resisting design concept. In addition, blast simulation of FRP retrofitted RC panel is performed to validate the proposed model and analysis method. For validation of the proposed model and analysis method, the reported experimental results are compared with the debonding failure analysis results. From the comparative verification, it is confirmed that the proposed analytical model considering debonding failure of FRP is able to reasonably predict the behavior of FRP retrofitted concrete panel under blast loading.

• The Korean Journal of Applied Statistics
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• v.13 no.2
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• pp.505-514
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• 2000

A Markov Chain Monte Carlo method with data augmentation is developed to compute the features of the posterior distribution. For each observed failure epoch, we introduced mixture failure model of Rayleigh and Erlang(2) pattern. This data augmentation approach facilitates specification of the transitional measure in the Markov Chain. Gibbs steps are proposed to perform the Bayesian inference of such models. For model determination, we explored sum of relative error criterion that selects the best model. A numerical example with simulated data set is given.

• Proceedings of the Korean Society For Composite Materials Conference
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• 2005.11a
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• pp.75-78
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• 2005

Using a low-energy Ar+ ion-beam with and without reactive gases, polymers such as chemically stable poly(ether ether ketone) (PTFE) and poly(ether ether ketone) (PEEK) films were modified to have special surface features. The adhesion strength between the polymers and the copper was significantly improved because of both changes in the surface topography and chemical interactions due to polymer surface functionalization (oxidation and amination). The surface modification altered the failure mode from adhesive failure for the unmodified polymer/Cu interface to cohesive failure for the surface-modified polymer/Cu layer interface..

• Nuclear Engineering and Technology
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• v.44 no.8
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• pp.961-970
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• 2012

Often, probabilistic fracture mechanics (PFM) approaches have been adopted to quantify the failure probabilities of Ni-base alloy components, especially due to primary water stress corrosion cracking (PWSCC), in a primary piping system of pressurized water reactors. In this paper, the key features of an advanced PFM code, PINEP-PWSCC (Probabilistic INtegrity Evaluation for nuclear Piping-PWSCC) for such purpose, are described. In developing the code, we adopted most recent research results and advanced models in calculation modules such as PWSCC crack initiation and growth models, a performance-based probability of detection (POD) model for Ni-base alloy welds, and so on. To verify the code, the failure probabilities for various Alloy 182 welds locations were evaluated and compared with field experience and other PFM codes. Finally, the effects of pre-existing crack, weld repair, and POD models on failure probability were evaluated to demonstrate the applicability of PINEP-PWSCC.

• Journal of Information Processing Systems
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• v.15 no.6
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• pp.1489-1502
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• 2019

This work introduces a novel unweighted combination method (UCSS) for business failure perdition (BFP). With considering features of BFP in the age of big data, UCSS integrates the quantitative and qualitative analysis by utilizing soft set theory (SS). We adopt the conventional expert system (ES) as the basic qualitative classifier, the logistic regression model (LR) and the support vector machine (SVM) as basic quantitative classifiers. Unlike other traditional combination methods, we employ soft set theory to integrate the results of each basic classifier without weighting. In this way, UCSS inherits the advantages of ES, LR, SVM, and SS. To verify the performance of UCSS, it is applied to real datasets. We adopt ES, LR, SVM, combination models utilizing the equal weight approach (CMEW), neural network algorithm (CMNN), rough set and D-S evidence theory (CMRD), and the receiver operating characteristic curve (ROC) and SS (CFBSS) as benchmarks. The superior performance of UCSS has been verified by the empirical experiments.

• Journal of the Korean Society of Safety
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• v.22 no.3 s.81
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• pp.74-80
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• 2007

In this study, a documentary survey, face mapping, and stability analysis were performed on the collapsed colluvial soil slope. The purpose of this paper is to identify the cause of slope failure and determine slope stability for similar areas. Boring samples were extracted from the slump and laboratory tests were performed to find out the cause of slope failure. In addition, the limit equilibrium method was used in order to determine the stability of the slope. As a result of this investigation and the analysis of data, the type of collapse and cause of slope failure have been shown to have a strong correlation with the natural geographical and geological features which make up the collapse profile of the study area. These results will help to develop guidelines for formulating countermeasure methods.

• Structural Engineering and Mechanics
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• v.37 no.1
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• pp.79-93
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• 2011

A simple mechanical model is proposed to demonstrate qualitatively the pancake progressive collapse of multi-storey structures. The impact between two collapsed storeys is simulated using a simple algorithm that builds on virtual mass-spring-damper system. To analyze various collapse modes, columns and beams are considered separately. Parametric studies show that the process of progressive collapse involves a large number of complex mechanisms. However, the proposed model provides a simple numerical tool to assess the overall behavior of collapse arising from a few initiating causes. Unique features, such as beam-to-beam connection failure criterion, and beam-to-column connection failure criterion are incorporated into the program. Besides, the criterion of local failure of structural members can also be easily incorporated into the proposed model.

• Structural Monitoring and Maintenance
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• v.6 no.2
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• pp.125-145
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• 2019

Bridge scour is one of the predominant causes of bridge failure. Current climate deterioration leads to increase of flooding frequency and severity and thus poses a higher risk of bridge scour failure than before. Recent studies have explored extensively the vibration-based scour monitoring technique by analyzing the structural modal properties before and after damage. However, the state-of-art of this area lacks a systematic approach with sufficient robustness and credibility for practical decision making. This paper attempts to develop a data-driven methodology for bridge scour monitoring using support vector machines. This study extracts features from the bridge dynamic responses based on a generic sensitivity study on the bridge's modal properties and selects the features that are significantly contributive to bridge scour detection. Results indicate that the proposed data-driven method can quantify the bridge scour damage with satisfactory accuracy for most cases. This paper provides an alternative methodology for bridge scour evaluation using the machine learning method. It has the potential to be practically applied for bridge safety assessment in case that scour happens.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.3
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• pp.359-369
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• 2022

In slope stability analysis for landslides, mountains have various slopes and geographical features, and hence it is necessary to estimate stability using rigorous analysis methods. In this study, after the analysis of infiltration behavior through unsaturated layers due to rainfall, the stability of landslide was estimated to account for the variation of pore water pressures. In the analysis of slope stability, a three-dimensional slope analysis was compared with an infinite slope analysis in a case study of terrain in which an actual landslide occurred. In the three-dimensional slope stability analysis, it was found that the location of the failure and the failure area were predicted accurately based on the detailed geological information despite the variation of geographical features.