uncertainty measure
Recently Published Documents


TOTAL DOCUMENTS

196
(FIVE YEARS 62)

H-INDEX

21
(FIVE YEARS 6)

TecnoLógicas ◽  
2021 ◽  
Vol 24 (52) ◽  
pp. e1910
Author(s):  
Alejandro Salgar-Marín ◽  
Javier Alberto Vargas ◽  
Andrés Felipe Ramírez-Barrera

In the present investigation, a scientific procedure was developed, and a mathematical model was proposed, with the objective of determining, under standard conditions, the uncertainty, and the measurement of dioptric power in ophthalmic lenses. The methodology of the scientific procedure is based on the fundamentals of geometric optics, this process guarantees and establishes a standardized uncertainty measure in repeatable and reproducible processes. The methodology is complemented with a proposed mathematical model based on the guide for the expression of uncertainty in measurement - GUM. This model can be applied to lenses used for calibrating eye care equipment (such as lensometers, which are used to diagnose myopia and farsightedness) by evaluating the lenses without having direct contact with patients. When the proposed mathematical model was applied, its experimental result was a maximum expanded uncertainty of ± 0.0079 diopters in a 0.5-diopter lens. This is optimal compared to the result of other authors this article, who reported a maximum expanded uncertainty of ± 0.0086 diopters. In conclusion, the application of this scientific procedure provides manufacturers and users of this type of lenses with a reliable measurement thanks to a calibration process based on geometrical optics and centered on patient safety.


2021 ◽  
Vol 9 ◽  
Author(s):  
Ci Zhang ◽  
Yilin Hu ◽  
Leping Huang ◽  
Yajie Huang

This paper examines the effects of the pandemics-related uncertainty on corporate innovation in Chinese firms. For this purpose, the recent uncertainty measure of pandemics, the Pandemics Discussion Index (PDI), is used. The findings from the fixed-effects estimations show the negative impact of the PDI on corporate innovation. Government subsidies, operation profits, and total exports also positively affect corporate innovation. In addition, firms' management efficiency promotes corporate innovation. These results hold when the Blundell-Bond estimations are utilized to address potential endogeneity. Various robustness analyses, such as considering the lagged PDI and the lagged controls, are also conducted. Consequently, the main results remain robust. Thus, this paper provides novel and robust evidence on the negative impact of pandemics on Chinese firms' corporate innovation behavior.


2021 ◽  
Author(s):  
Michael D Bauer ◽  
Aeimit K Lakdawala ◽  
Philippe Mueller

Abstract Uncertainty about future policy rates plays a crucial role for the transmission of monetary policy to financial markets. We demonstrate this using event studies of FOMC announcements and a new model-free uncertainty measure based on derivatives. Over the ‘FOMC uncertainty cycle’ announcements systematically resolve uncertainty, which then gradually ramps up again. Changes in monetary policy uncertainty around FOMC announcements—often due to forward guidance—have pronounced effects on asset prices that are distinct from the effects of conventional policy surprises. The level of uncertainty determines the magnitude of financial market reactions to surprises about the path of policy rates.


2021 ◽  
Vol 14 (11) ◽  
pp. 520
Author(s):  
Mohsen Bahmani-Oskooee ◽  
Jungho Baek

Since the introduction of the news-based policy uncertainty measure, a few studies have looked at its impact on trade flows by using panel models and aggregate trade data. In this paper we consider the short-run and long-run response of 61 2-digit U.S. exporting industries to Korea and 49 2-digit Korean exporting industries to the U.S. to policy uncertainty measures of the U.S. and Korea. We find that both measures have short-run effects on exports of almost one-third of industries in either direction. In the long run, however, while nine U.S. exporting industries (with a trade share of 9%) are negatively affected by the Korean uncertainty measure, only five industries (with 6% export share) are affected by the U.S. uncertainty measure. As for the Korean exporting industries, we find that three industries with a 31% export share are affected positively by the Korean uncertainty measure and six industries with a 7% export share are affected positively by the U.S. uncertainty measure.


2021 ◽  
Author(s):  
Xiaozhuan Gao ◽  
Lipeng Pan ◽  
Yong Deng

Author(s):  
Ahmad Kamal Mohd Nor ◽  
Srinivasa Rao Pedapati ◽  
Masdi Muhammad

XAI is presently in its early assimilation phase in Prognostic and Health Management (PHM) domain. However, the handful of PHM-XAI articles suffer from various deficiencies, amongst others, lack of uncertainty quantification and explanation evaluation metric. This paper proposes an anomaly detection and prognostic of gas turbines using Bayesian deep learning (DL) model with SHapley Additive exPlanations (SHAP). SHAP was not only applied to explain both tasks, but also to improve the prognostic performance, the latter trait being left undocumented in the previous PHM-XAI works. Uncertainty measure serves to broaden explanation scope and was also exploited as anomaly indicator. Real gas turbine data was tested for the anomaly detection task while NASA CMAPSS turbofan datasets were used for prognostic. The generated explanation was evaluated using two metrics: Local Accuracy and Consistency. All anomalies were successfully detected thanks to the uncertainty indicator. Meanwhile, the turbofan prognostic results show up to 9% improvement in RMSE and 43% enhancement in early prognostic due to SHAP, making it comparable to the best published methods in the problem. XAI and uncertainty quantification offer a comprehensive explanation package, assisting decision making. Additionally, SHAP ability in boosting PHM performance solidifies its worth in AI-based reliability research.


Sign in / Sign up

Export Citation Format

Share Document