• Nuclear Engineering and Technology
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• v.46 no.6
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• pp.773-782
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• 2014

The general path model (GPM) is one approach for performing degradation-based, or Type III, prognostics. The GPM fits a parametric function to the collected observations of a prognostic parameter and extrapolates the fit to a failure threshold. This approach has been successfully applied to a variety of systems when a sufficient number of prognostic parameter observations are available. However, the parametric fit can suffer significantly when few data are available or the data are very noisy. In these instances, it is beneficial to include additional information to influence the fit to conform to a prior belief about the evolution of system degradation. Bayesian statistical approaches have been proposed to include prior information in the form of distributions of expected model parameters. This requires a number of run-to-failure cases with tracked prognostic parameters; these data may not be readily available for many systems. Reliability information and stressor-based (Type I and Type II, respectively) prognostic estimates can provide the necessary prior belief for the GPM. This article presents the Bayesian updating framework to include prior information in the GPM and compares the efficacy of including different information sources on two data sets.

• The Korean Journal of Food And Nutrition
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• v.29 no.6
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• pp.952-961
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• 2016

The objective of this study is to examine the effects of consumer beliefs regarding three food certifications on their behavioral intention and the behavioral intention biases to purchase (purchasing intention biases) certified agricultural products as predicted by a subjective probability model. The food certifications used for this study are 'Organic food', 'Traceability system of food products,' and 'Hazard Analysis Critical Control Point (HACCP)'. Tofu (bean curd) was selected as being representative of agricultural food products, for the purposes of this study. In 2016, we surveyed 243 consumers regarding the strength of their belief regarding their prior beliefs relative to each certification, as well as the strength of their intention to purchase certified tofu based on their belief strengths for this study. The study resulted in the following findings: Firstly, consumers hold more than two different prior beliefs for each of the three certifications included in this study. Consumers' prior beliefs regarding these certifications have an impact on their consideration as to whether they plan to buy those certified agricultural products. Secondly, consumers try to persuade themselves to ensure that their particular belief about the product's certification could lead to a purchasing decision regarding that agricultural product.

• Journal of The Korean Association For Science Education
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• v.25 no.2
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• pp.111-121
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• 2005

The purpose of this study was to analyze characteristics of experimental design and evidence choice of the elementary school students in problem solving process related to controlling variable. For this study, 96 6th grade students were selected and tested with Science Reasoning Task. This study revealed that the types of experimental design were categorized as variance of control variable, controlling of causal variable, perfect controlling variable, imperfect controlling variable, variance of all variable. Prior belief had a strong influence on student's experimental design. The types of evidence choice were categorized as perfect controlling variable, controlling causal variable, variance of causal variable. The degree of controlling variable in evidence choice process was much lower than that in experimental design. Most students tended to choose evidence according to prior belief without controlling variable. The results of this study implied that student's prior belief and characteristic of science process skills should be considered to develop program for promoting controlling variable ability.

• Journal of applied mathematics & informatics
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• v.40 no.3_4
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• pp.515-530
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• 2022

A factor graph and belief propagation can be used for finding stochastic values of link weights in biological networks. However it is not easy to follow the process of use and so we presented the process with a toy network of three nodes in our prior work. We extend this work more generally and present numerical example for a network of 100 nodes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.9
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• pp.4405-4418
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• 2016

Automatic image completion techniques have difficulty processing images in which the target region has multiple planes or is non-facade. Here, we propose a new image completion method that uses belief propagation based on planar priorities. We first calculate planar information, which includes planar projection parameters, plane segments, and repetitive regularity extractions within the plane. Next, we convert this planar information into planar guide knowledge using the prior probabilities of patch transforms and offsets. Using the energy of the discrete Markov Random Field (MRF), we then define an objective function for image completion that uses the planar guide knowledge. Finally, in order to effectively optimize the MRF, we propose a new optimization scheme, termed Planar Priority-belief propagation that includes message-scheduling-based planar priority and dynamic label cropping. The results of experiment show that our approach exhibits advanced performance compared with existing approaches.

• Communications for Statistical Applications and Methods
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• v.28 no.4
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• pp.315-327
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• 2021

The Spatial Autoregressive (SAR) models have drawn considerable attention in recent econometrics literature because of their capability to model the spatial spill overs in a feasible way. While considering the Bayesian analysis of these models, one may face the problem of lack of robustness with respect to underlying prior assumptions. The generalized Bayes estimators provide a viable alternative to incorporate prior belief and are more robust with respect to underlying prior assumptions. The present paper considers the SAR model with a set of linear restrictions binding the regression coefficients and derives restricted generalized Bayes estimator for the coefficients vector. The minimaxity of the restricted generalized Bayes estimator has been established. Using a simulation study, it has been demonstrated that the estimator dominates the restricted least squares as well as restricted Stein rule estimators.

• Journal of the Korean Society of Hazard Mitigation
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• v.7 no.4
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• pp.31-39
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• 2007

Disaster mythology is "beliefs about human behavior in disaster that have been proven to be wrong through scientifically conducted research studies." Disaster researchers have discovered a series of disaster myths. The results of research survey based on 491 individuals confirm prior research representing widespread belief in disaster mythology such as panic, looting, crime, evacuation and lethargy. This study also indicates that, while high, the percentage of local government officials demonstrating belief in disaster myths was lower than the public except for looting. The probability of believing disaster myths was greater for individuals who were female (panic and evacuation), old (evacuation and lethargy), in their twenties and thirties (looting), and officials with disaster related work experience (panic, looting and crime). The results indicate the importance of understanding public belief to make effective emergency plans.

• Journal of muscle and joint health
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• v.30 no.2
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• pp.70-82
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• 2023

Purpose: This study aims to systematically clarify and enhance the understanding of osteoporosis prevention interventions based on Health Belief Model (HBM). The analysis includes HBM constructs, intervention characteristics, and outcomes from prior studies. Methods: We extensively searched eight electronic databases to identify peer-reviewed studies that implemented HBM-based interventions for osteoporosis prevention until June 2023. Results: Initially, 638 articles were identified, and after a rigorous evaluation process, 11 articles were included in the evidence synthesis. The analysis revealed that HBM-based interventions significantly improved likelihood of taking action including knowledge, HBM constructs and adopting preventive behaviors such as calcium intake and exercise. However, most interventions included in this study did not fully encompass all five HBM constructs or specify the particular components adopted. Conclusion: There is a need for additional research and intervention refinement for a more comprehensive understanding of osteoporosis preventive interventions. This should involve a concerted effort to incorporate all HBM constructs into the context of osteoporosis prevention. Thus, more effective interventions promoting optimal preventive behaviors and reducing the burden of osteoporosis can be developed.

• Asia pacific journal of information systems
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• v.12 no.2
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• pp.45-68
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• 2002

Technology adoption for information appliance, which is expected to grow rapidly in the near future, is different from other technologies in that it is mainly used in the home environment when the customers haven't experienced it before. This paper finds important variables from prior research about technology adoption and develops a measurement model that fits for the information appliance. Pretest and pilot studies for the model is conducted in order to guarantee content validity, reliability, convergent validity and discriminant validity. Finally, LISREL analysis is used for finding out the causality among variables and testing for model fitness. The results indicate that three factors that influence behavioral intention are attitude, subjective norm and perceived behavioral control. Attitude is influenced by attitudinal belief, which consists of perceived usefulness, trialability, result demonstrability, image and enjoyment. Perceived behavioral control is influenced by control belief that consists of rapid change in technology, cost and ease of use. This paper ends with implications and limitations of study results.

• Journal of Korean Neurosurgical Society
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• v.50 no.5
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• pp.403-408
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• 2011

Objective : Contrary to some clinical belief, there were quite a few studies regarding animal models of intracerebral hemorrhage (ICH) $in$ $vivo$ suggesting that prior use of statins may improve outcome after ICH. This study reports the effect of 3-hydroxy-3-methyl-glutaryl-coenzyme A (HMG CoA) reductase inhibitor, simvastatin given before experimental ICH. Methods : Fifty-one rats were subjected to collagenase-induced ICH, subdivided in 3 groups according to simvastatin treatment modality, and behavioral tests were done. Hematoma volume, brain water content and hemispheric atrophy were analyzed. Immunohistochemical staining for microglia (OX-42) and endothelial nitric oxide synthase (eNOS) was performed and caspase-3 activity was also measured. Results : Pre-simvastatin therapy decreased inflammatory reaction and perihematomal cell death, but resulted in no significant reduction of brain edema and no eNOS expression in the perihematomal region. Finally, prior use of simvastatin showed less significant improvement of neurological outcome after experimental ICH when compared to post-simvastatin therapy. Conclusion : The present study suggests that statins therapy after ICH improves neurological outcome, but prior use of statins before ICH might provide only histological improvement, providing no significant impact on neurological outcome against ICH.