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Purpose: Tourism that inherently has human interaction and mobility is more at risk than any other industries. Because of its highly competitive nature, tourism has to be prepared to deal with problems. Study design/methodology/approach: In this developmental-applied study, the researchers tried to consider the extent of the COVID-19 pandemic as a global crisis by Fuzzy Cognitive Mapping technique (FCM). Findings: According to the findings, confidence building propaganda action plan, tax forgiveness, and payment of subsidies and support, the need to take knowledge of crisis management seriously, forming a crisis management team, and target market design are the most important strategies for overcoming the corona crisis. Originality/value: The findings of the present study may have some significant theoretical and practical implications for risk management students and experts. Keywords: COVID-19, Crisis Pathology, Tourism Risk Management, Fuzzy Cognitive Mapping Technique (FCM)

Background: Exposure to noise can increase biological stress reactions and that could increase the risk of stress-related prenatal effects, including adverse obstetric outcomes; however, the association between exposure to noise and adverse obstetric outcomes has not been extensively explored. The objective of this review was to evaluate the evidence between noise exposures and adverse obstetric outcomes, specifically preeclampsia, gestational diabetes, and gestational hypertension.Materials and Methods: A systematic review of English language, comparative studies available in PubMed, Cochrane Central, EMBASE, and CINAHL databases between January 1, 1980 and December 29, 2021 was performed. Risk of bias for individual studies was assessed using the Risk of Bias Instrument for Nonrandomized Studies of Exposures, and the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach was used to assess the certainty of the body of evidence for each outcome.Results: Six studies reporting on preeclampsia, gestational diabetes, and gestational hypertension were identified. Although some studies suggested there may be signals of increased responses to increased noise exposure for preeclampsia and gestational hypertension, the certainty in the evidence of an effect of increased noise on all the outcomes was very low due to concerns with risk of bias, inconsistency across studies, and imprecision in the effect estimates.Conclusions: While the certainty of the evidence for noise exposure and adverse obstetric outcomes was very low, the findings from this review may be useful for directing further research in this area, as there is currently limited evidence available. These findings may also be useful for informing guidelines and policies involving noise exposure situations or environments. [ABSTRACT FROM AUTHOR]

Background: : Exposure to acute noise can cause an increase in biological stress reactions, which provides biological plausibility for a potential association between sustained noise exposure and stress-related health effects. However, the certainty in the evidence for an association between exposures to noise on short- and long-term biomarkers of stress has not been widely explored. The objective of this review was to evaluate the strength of evidence between noise exposure and changes in the biological parameters known to contribute to the development of stress-related adverse cardiovascular responses.Materials and Methods: This systematic review comprises English language comparative studies available in PubMed, Cochrane Central, EMBASE, and CINAHL databases from January 1, 1980 to December 29, 2021. Where possible, random-effects meta-analyses were used to examine the effect of noise exposure from various sources on stress-related cardiovascular biomarkers. The risk of bias of individual studies was assessed using the risk of bias of nonrandomized studies of exposures instrument. The certainty of the body of evidence for each outcome was assessed using the Grading of Recommendations Assessment, Development, and Evaluation approach.Results: : The search identified 133 primary studies reporting on blood pressure, hypertension, heart rate, cardiac arrhythmia, vascular resistance, and cardiac output. Meta-analyses of blood pressure, hypertension, and heart rate suggested there may be signals of increased risk in response to a higher noise threshold or incrementally higher levels of noise. Across all outcomes, the certainty of the evidence was very low due to concerns with the risk of bias, inconsistency across exposure sources, populations, and studies and imprecision in the estimates of effects.Conclusions: : This review identifies that exposure to higher levels of noise may increase the risk of some short- and long-term cardiovascular events; however, the certainty of the evidence was very low. This likely represents the inability to compare across the totality of the evidence for each outcome, underscoring the value of continued research in this area. Findings from this review may be used to inform policies of noise reduction or mitigation interventions. [ABSTRACT FROM AUTHOR]

Background: Exposure to noise can increase biological stress reactions, which may increase adverse health effects, including metabolic disorders; however, the certainty in the association between exposure to noise and metabolic outcomes has not been widely explored. The objective of this review is to evaluate the evidence between noise exposures and metabolic effects. Materials and Methods: A systematic review of English and comparative studies available in PubMed, Cochrane Central, EMBASE, and CINAHL databases between January 1, 1980 and December 29, 2021 was performed. Risk of Bias of Nonrandomized Studies of Exposures was used to assess risk of bias of individual studies and certainty of the body of evidence for each outcome was assessed using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach. Results: Fifty-six primary studies reporting on cortisol, cholesterol levels, waist circumference, glucose levels, and adrenaline and/or noradrenaline were identified. Although meta-analyses suggested that there may be an increase in waist circumference and adrenaline with increased noise exposure, the certainty in the evidence is very low. Overall, the certainty in the evidence of an effect of increased noise on all the outcomes were low to very low due to concerns with risk of bias, inconsistency across exposure sources, populations, and studies, and imprecision in the estimates of effects. Conclusions: The certainty of the evidence of increased noise on metabolic effects was low to very low, which likely reflects the inability to compare across the totality of the evidence for each outcome. The findings from this review may be used to inform policies involving noise reduction and mitigation strategies, and to direct further research in areas that currently have limited evidence available. [ABSTRACT FROM AUTHOR]

Experiments to obtain input/output data for system identification of some systems can be conducted only with the controllers in action. Estimating an open-loop system model using closed-loop data offers many difficulties, particularly when noise is present in the measurements. In this paper, a new indirect non-linear system identification technique using a non-linear auto regressive moving average with exogenous input (NARMAX) structure and employing input/output data obtained from closed-loop experiments is described for the first time. Furthermore, a new method to estimate the linear multivariable open-loop transfer function from closed-loop data using an algebraic equation set is presented. The effectiveness of the proposed linear and non-linear identification approaches is illustrated by simulation studies on a non-linear physical system. [ABSTRACT FROM AUTHOR]

System identification can be carried out by perturbing the system input(s) and processing the recorded input(s) and output(s) of the system. In synchronous generators, if the governor is not in action, one of the inputs (the mechanical torque) is not available for measurement, and the experiments cannot be carried out. In the published literature, the input perturbation is mostly carried out through the excitation system, and the mechanical torque is assumed to be constant during the experiment. This would affect the accuracy of the results. In this paper, various multivariable closed-loop identification methods (direct and indirect and linear and nonlinear) are used to obtain an accurate and comprehensive model for the synchronous generator. To simplify model structure, the orthogonal least squares with D-optimality method is used to remove unnecessary terms. A comparison of the performance of various techniques shows that closed-loop nonlinear identification using nonlinear auto regressive with exogenous input polynomials is very effective, and a simple nonlinear model for the synchronous generator can be identified successfully using multivariable closed-loop input and output data. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]