Threshold Estimation Research Articles

Intelligent fault monitoring and diagnosis of tunnel fans using a hierarchical cascade forest

Tunnel fan is critical fire-fighting equipment, and its safe and stable operation is very important for the efficiency and safety of tunnel traffic. Existing studies commonly train the fault diagnosis methods with the goal of minimizing mean error which ignores the difference between classes in feature distribution. To solve the problem of inaccurate prediction caused by mean error evaluation, this paper presents a non-neural deep learning model, namely hierarchical cascade forest, which has three characteristics: (1) A hierarchical cascade structure is constructed, of which the output comes from each layer; (2) Each fault class is evaluated and recognized independently, the result of fault classes that are easy to distinguish is output earlier; (3) A confidence-based threshold estimate method is proposed in HCF and used to improve the training method to increase the reliability of HCF. Based on these, HCF improves the cascade forest structure and implements the proper matching of different depth of feature and fault patterns. The effect of HCF is verified through experiments based on the tunnel fans testing rig. Experimented results show that, compared to Deep Forest, the accuracy of HCF increases by 0.6% to 10.8%, and the training time of HCF is reduced 33.24%.

Risk scores’ performance and their impact on operative decision-making in left-sided endocarditis: a cohort study

The accuracy of contemporary risk scores in predicting perioperative mortality in infective endocarditis (IE) remains controversial. The aim is to evaluate the performance of existent mortality risk scores for cardiovascular surgery in IE and the impact on operability at high-risk thresholds. A single-center retrospective review of adult patients diagnosed with acute left-sided IE undergoing surgery from May 2014 to August 2019 (n = 142) was done. Individualized risk calculation was obtained according to the available mortality risk scores: EuroScore I and II, PALSUSE, Risk-E, Costa, De Feo-Cotrufo, AEPEI, STS-risk, STS-IE, APORTEI, and ICE-PCS scores. A cross-validation analysis was performed on the score with the best area under the curve (AUC). The 30-day survival was 96.5% (95%CI 91–98%). The score with worse area under the curve (AUC = 0.6) was the STS-IE score, while the higher was for the RISK-E score (AUC = 0.89). The AUC of the majority of risk scores suggested acceptable performance; however, statistically significant differences in expected versus observed mortalities were common. The cross-validation analysis showed that a large number of survivors (> 75%) would not have been operated if arbitrary high-risk threshold estimates had been used to deny surgery. The observed mortality in our cohort is significantly lower than is predicted by contemporary risk scores. Despite the reasonable numeric performance of the analyzed scores, their utility in judging the operability of a given patient remains questionable, as demonstrated in the cross-validation analysis. Future guidelines may advise that denial of surgery should only follow a highly experienced Endocarditis Team evaluation.

Impact of financial inclusion on banking stability in ASEAN countries –threshold financial inclusion

ABSTRACT This paper aims to investigate the effect of financial inclusion on bank stability in ASEAN countries. FEM, threshold estimation, and GMM method, respectively. The findings show that financial inclusion decreases the stability of banks, but the influence varies between banks and market structures. Furthermore, we examine the impact of the financial inclusion threshold on bank stability. The results show countries with financial inclusion above the threshold will increase stability, whereas countries with financial inclusion below the threshold will decrease the bank’s strength. Research on the non-linear impact of financial inclusion on bank stability through threshold model.

Estimating health system opportunity costs: the role of non-linearities and inefficiency

BackgroundEmpirical estimates of health system opportunity costs have been suggested as a basis for the cost-effectiveness threshold to use in Health Technology Assessment. Econometric methods have been used to estimate these in several countries based on data on spending and mortality. This study examines empirical evidence on four issues: non-linearity of the relationship between spending and mortality; the inclusion of outcomes other than mortality; variation in the efficiency with which expenditures generate health outcomes; and the relationship among efficiency, mortality rates and outcome elasticities.MethodsQuantile Regression is used to examine non-linearities in the relationship between mortality and health expenditures along the mortality distribution. Data Envelopment Analysis extends the approach, using multiple measures of health outcomes to measure efficiency. These are applied to health expenditure data from 151 geographical units (Primary Care Trusts) of the National Health Service in England, across eight different clinical areas (Programme Budget Categories), for 3 fiscal years from 2010/11 to 2012/13.ResultsThe results suggest differences in efficiency levels across geographical units and clinical areas as to how health resources generate outcomes, which indicates the capacity to adjust to a decrease in health expenditure without affecting health outcomes. Moreover, efficient units have lower absolute levels of mortality elasticity to health expenditure than inefficient ones.ConclusionsThe policy of adopting thresholds based on estimates of a single system-wide cost-effectiveness threshold assumes a relationship between expenditure and health outcomes that generates an opportunity cost estimate which applies to the whole system. Our evidence of variations in that relationship and therefore in opportunity costs suggests that adopting a single threshold may exacerbate the efficiency and equity concerns that such thresholds are designed to counter. In most health care systems, many decisions about provision are not made centrally. Our analytical approach to understanding variability in opportunity cost can help policy makers target efficiency improvements and set realistic targets for local and clinical area health improvements from increased expenditure.

Intra-rater reliability of pressure pain threshold using a digital algometer

BackgroundPressure Pain Thresholds (PPT) has been the main sensory modality studied in headache disorders. It is usually repetitive, leading to potential variability between measurements. Since threshold estimation relies on the observer, patient, body site, and the device used, it is important to assess measurement reliability in the specific clinical and methodological scenario to be studied in order to minimize error. ObjectiveThe aim of this study is to confirm intra-rater reliability of PPT in the head of adults using a digital algometer device. MethodsPPT was measured with a digital algometer in 3 consecutive assessments conducted 10 min apart. Eight sites were measured in each time at the occipital, temporal and masseter regions bilaterally, frontal and vertex at midline. The reliability using intra-class variability (ICC) and covariance were calculated between times 1, 2, 3, and all times versus the mean. Scores above 0,75 were considered as having excellent reliability. ResultsTen healthy volunteers aged (21-55) were studied. The sum of all sites measured in the head was 2182 (+-672) KPa for the first measure, 2085 (+- 626) KPa for the second, 2185 (+-685) for the third, and 2150 (+-685) KPa for the mean. All ICC coefficients calculated were 0,975 or higher in all areas. ConclusionsWe concluded that one PPT measure in the head with a digital algometer is as reliable as 3 repetitive measures The intra-rater reliability for PPT is considered excellent. Future studies assessing pain vulnerability or predicting headache occurrence can be performed without a significant risk of bias. Keywords: Pressure PainThreshold, Algometry, Reliability, Intra-class.

Clinical comparison of two automated audiometry procedures.

ObjectiveAutomated pure-tone audiometry has been shown to provide similar hearing threshold estimates to conventional audiometry, but lower correlations were reported at high and low frequencies in audiometric tests than those of manual tests, while the correlations were better in the middle frequencies. In this paper, we used the same equipment and different test procedures for automated testing, and compared the results with manual test results.DesignOne hundred subjects aged 18–36 years were randomly divided into two groups to perform air-conduction pure-tone audiometry (0.25, 0.5, 1, 2, 4, 8 kHz) using the ascending and shortened ascending protocols built-in to the automated audiometer, respectively. Recorded testing time, the total number of responses and the subject’s preference tests were compared with those of manual tests.ResultsSignificant difference was found at 250 Hz regarding the distribution of the absolute difference between the two automated and the manual thresholds. The testing time spend in the ascending method (9.8 ± 1.4 min, mean ± SD) was significantly longer than in the shorted ascending method (5.8 ± 0.9 min). The total numbers of responses of the ascending method (90.5 ± 10.8 times) and shorted ascending method (62.0 ± 11.4 times) were significantly different. Finally, no significant difference was found in preferences between automated and manual procedures.ConclusionThe shorted ascending method can save lots of testing time. The difference between the two automated thresholds at 250 Hz is caused by the different test procedures, and the difference at 8,000 Hz between the automated test and the manual test can be due to the transducer types and allowable differences in calibration.

The psychology of income wealth threshold estimations: A registered report.

How do people estimate the income that is needed to be rich? Two correlative survey studies (Study 1 and 2, N=568) and one registered experimental study (Study 3, N=500) examined the cognitive mechanisms that are used to derive an answer to this question. We tested whether individuals use their personal income (PI) as a self-generated anchor to derive an estimate of the income needed to be rich (= income wealth threshold estimation, IWTE). On a bivariate level, we found the expected positive relationship between one's PI and IWTE and, in line with previous findings, we found that people do not consider themselves rich. Furthermore, we predicted that individuals additionally use information about their social status within their social circles to make an IWTE. The findings from study 2 support this notion and show that only self-reported high-income individuals show different IWTEs depending on relative social status: Individuals in this group who self-reported a high status produced higher IWTEs than individuals who self-reported low status. The registered experimental study could not replicate this pattern robustly, although the results trended non-significantly in the same direction. Together, the findings revealed that the income of individuals as well as the social environment are used as sources of information to make IWTE judgements, although they are likely not the only important predictors.

Multi-threshold proportional hazards model and subgroup identification.

We propose a novel two-stage procedure for change point detection and parameter estimation in a multi-threshold proportional hazards model. In the first stage, we estimate the number of thresholds by formulating the threshold detection problem as a variable selection problem and applying the penalized partial likelihood approach. In the second stage, the change point locations are refined by a grid search and the standard inference for segment regression can then follow. The proposed model and estimation procedure could lend support to subgroup identification and personalized treatment recommendation in medical research. We establish the consistency of the threshold estimators and regression coefficient estimators under technical conditions. The finite sample performance of the method is demonstrated via simulation studies and two cancer data examples.

Non-linearity and the threshold effect of transparency on economic growth: evidence from developing countries

ABSTRACT This study examines the linear and non-linear threshold impacts of transparency on economic growth in 70 developing countries from 1984 through 2018, utilizing panel generalized method of moments (GMM) and dynamic-panel threshold estimations. We find that the impact of transparency on growth is stronger when we use non-linear GMM, and dynamic-panel threshold estimations. There is a U-shaped relationship between transparency and economic growth, while transparency is found to stimulate economic growth, especially in a high-transparency threshold regime. The result reveals that financial development plays an important role in moderating the transparency–economic growth nexus in developing countries.

Estimation of rheological percolation threshold and influence of fibre length on properties of polypropylene/sisal fibre composites having near critical fibre length

In this paper, the rheological percolation threshold and the hardness of Polypropylene/Sisal fibre (PP/SF) composites were correlated. Power law fit was implemented for the estimation of rheological percolation threshold. Further, the performance properties of PP/SF composites having near-critical length fibre (NCLF) and short fibre were investigated in terms of thermomechanical, rheological, and dynamic mechanical parameters. The Shore D hardness data revealed that the rheological percolation threshold of the prepared composites remained in the range of 20–30 wt% of sisal fibre. Moreover, sisal fibre had an undeniable impact on the dynamic mechanical properties of the prepared composites. Further, the rise in the onset degradation temperature by 40 °C proved the improvement in thermal stability of the prepared composites. It was also found that PP/SF composite having 20 wt% of near critical length fibre had properties equivalent to that of PP/SF composite having 40 wt% of short fibre (fibre length less then critical fibre length). • Correlation between Rheological Percolation threshold and Shore D hardness. • PP/SF composites having near critical length fibres. • Effect of fibre length on performance properties of PP/SF composites.

Comparison of Ventilatory and Blood Lactate Thresholds in Elite Soccer Players

Despite a long research history, the lactate threshold continues to be a widely controversial field. Notwithstanding the controversies and influence of multiple determinants, the estimation of lactate threshold in sports has been considered one of the essential parameters in the prescription of training intensity, load monitoring, and perfor- mance prediction. The study aimed to compare the anaerobic ventilatory and lactate thresholds as determined by different methods in elite soccer players. The study consisted of twenty-five division 1 elite soccer players. The players were separated into two groups based on their run times on the treadmill. Group 1 (age 24.38±7.33 years, height 180.33±7.03 cm, weight 75.53±7.68 kg) consisted of players who completed more than 17 minutes on the treadmill, while group 2 (age 25.11±6.07 years, height 182.11±10.03 cm, weight 79.72±7.54 kg) consisted of those who completed less than 17 minutes. The players completed an incremental maximal cardiopulmonary exercise testing from which ventilatory thresholds were determined. Furthermore, measurements of blood samples were obtained every 3 minutes after completing each stage of the test, with a total of 141 measurements completed. Multivariate tests indicated no significant differences in the speeds calculated with ventilatory and lactate thresh- old methods. These findings suggest that the anaerobic ventilatory threshold (VT2) can be used as an alternative to the invasive lactate threshold measurements. Therefore, identifying a threshold point without utilizing an inva- sive procedure enhances the potential application of the VT2 or respiratory compensation point.

On Bayesian thresholding and truncation methods

Thresholding dynamic process is a powerful statistical tool for modeling structural nonlinear relationships. We here discuss a Bayesian formalism to give rise to a type of threshold estimation in dynamic process with spatial structure. A prior distribution is imposed on the unknown parameter of process model, designed to capture the sparseness of process parameters that is common to most application. For the prior specified, the posterior distribution yields a thresholding procedure. In this paper, we introduce a general approach in which the truncation step is directly implanted to MCMC procedure by thresholding the MCMC outputs. The proposed thresholding approach is applied to the basal topography of the Northeast Ice-Stream in Greenland by using Daubechies wavelet-based analysis.

Feedforward and Feedback Modulations Based Foveated JND Estimation for Images

The just noticeable difference (JND) reveals the key characteristic of visual perception, which has been widely used in many perception-based image and video applications. Nevertheless, the modulatory mechanism of the human visual system (HVS) has not been fully exploited in JND threshold estimation, which results in the existing JND models not being accurate enough. In this article, by analyzing the feedforward and feedback modulatory behaviors in the HVS, an enhanced foveated JND (FJND) estimation model is proposed considering modulatory effects and masking effects in visual perception. The contributions of this article are mainly twofold. On the one hand, by analyzing the modulatory behaviors in the HVS, the modulatory mechanism is incorporated into JND estimation and a hierarchical modulation-based JND estimation framework is proposed for the first time. On the other hand, according to the response characteristics of visual neurons, modulatory effects on visual sensitivity are formulated as several modulatory factors to modulate the estimated JND threshold properly. Compared with existing models, the proposed model is developed in view of not only the masking effects but also the modulatory effects, which makes our model more consistent with the HVS. For different complex input images, experimental results show that the proposed FJND model tolerates more distortion at the same perceptual quality in comparison with other existing models.

A generically parameterized model of Lake eutrophication: The impact of Stoichiometric ratios and constraints on the abundance of natural phytoplankton communities (GPLake-S)

Water quality improvement to avoid excessive phytoplankton blooms often requires eutrophication management where both phosphorus (P) and nitrogen (N) play a role. While empirical eutrophication studies and ecological resource competition theory both provide insight into phytoplankton abundance in response to nutrient loading, they are not seamlessly linked in the current state of eutrophication research. We argue that understanding species competition for multiple nutrients and light in natural phytoplankton communities is key to assessing phytoplankton abundance under changing nutrient supply. Here we present GPLake-S, a mechanistic model rooted in ecological resource competition theory, which has only eight parameters and can predict chlorophyll-a to nutrient relationships for phytoplankton communities under N, P, N+P colimitation and light limitation. GPLake-S offers a simple mechanistic tool to make first estimates of chlorophyll-a levels and nutrient thresholds for generic lake properties, accounting for variation in N:P ratio preferences of phytoplankton species. This makes the model supportive of water management and policy.

Robust nonparametric estimation for the volatility of financial market

The occurrence of a macroeconomic policy would lead to a jump of financial data and the presence of jump behaviors might make the statistical methods for high-frequency sampling data to face new challenges. This paper will use the threshold function technique to disentangle the continuous part and the jump part from the high frequency financial data. Moreover, in the financial practices, the abnormal observations contained in the data could cause bias from nonparametric estimation based on least squares. The paper will employ the local M estimation to provide a robust estimator for the unknown diffusion coefficient of the diffusion model with jumps under high frequency sampling data. Under certain conditions for the initial values, this paper further considers one-step local M estimation for the unknown diffusion coefficient which can reduce the calculation quantity under the estimation efficiency. The Monte Carlo numerical simulation results verify that compared with the local linear threshold estimator, the threshold one-step local M estimator is more accurate and more robust. Finally, the threshold one-step local M estimator in this paper is applied to the Shanghai composite index of 2015 and 2020 in China and the Nasdaq index of 2020 in USA, which illustrates the method considered in this paper possesses good finite sample properties.

Do higher public debt levels reduce economic growth?

AbstractWhile the effect of higher public debt levels on economic growth has received much attention, the literature partly points to contradictory results. This paper applies meta‐regression methods to 816 estimates from 47 primary studies. The unweighted mean of the reported results suggests that a 10 percentage points increase in public‐debt‐to‐GDP is associated with a decline in annual growth rates by 0.14 percentage points, with a 95% confidence interval from 0.09 to 0.19 percentage points. However, we cannot reject a zero effect after correcting for publication bias. Furthermore, the meta‐regression analysis shows that tackling endogeneity between public debt and growth leads to less adverse effects of public debt. In testing for nonlinear effects, our results do not point to a uniform public‐debt‐to‐GDP threshold beyond which growth slows. Threshold estimates are sensitive to data and econometric choices. These findings imply a lack of evidence of a consistently negative growth effect of higher public‐debt‐to‐GDP. The main policy implication is that there should be caution with regard to “one‐size‐fits‐all” fiscal policy prescriptions in dealing with higher public debt levels.

About spectroscopy of CeF3:Nd3+ crystal and the first laser experiments with diode pumping

The CeF3 crystal samples activated by neodymium ions were grown by the Bridgman method and studied under diode pumping. Spectroscopic studies were carried out for calculations of the lasing threshold, because some data for these calculations were not available in the literature or are not quite correct. As a result, the spectroscopic data on the CeF3:Nd3+ crystal available in the literature have been supplemented and corrected. It has been determined that concentration quenching occurs at concentrations not higher than 1.5%. Based on the obtained data, the threshold of oscillations at the 4F3/2 → 4I11/2 transition of Nd3+ ions was estimated to be about 2.3 mJ. In the first experiments with diode pumping, lasing was obtained at a wavelength of 1064 nm on the CeF3:Nd3+ crystal with a slope efficiency of 25%. The obtained experimental results agree with the theoretical estimate of the lasing threshold.

Item parameter estimations for multidimensional graded response model under complex structures

Item parameter recovery in the compensatory multidimensional graded response model (MGRM) under simple and complex structures with rating-scale item response data was examined. A simulation study investigated factors that influence the precision of item parameter estimation, including sample size, intercorrelation between the dimensions, and test lengths for the MGRM under balanced and unbalanced complex structures, as well as the simple structure. The item responses for the MGRM were generated and analyzed across conditions using the R package mirt. The bias and root mean square error (RMSE) was used to evaluate item parameter recovery. Results suggested that item parameter estimation was more accurate in balanced complex structure conditions than in unbalanced or simple structures, especially when the test length was 40 items, and the sample size was large. Further, the mean bias and RMSE in the recovery of item threshold estimates along the two dimensions for both balanced and unbalanced complex structures were consistent across all conditions.

Threshold regression with nonparametric sample splitting

This paper develops a threshold regression model where an unknown relationship between two variables nonparametrically determines the threshold. We allow the observations to be cross-sectionally dependent so that the model can be applied to determine an unknown spatial border for sample splitting over a random field. We derive the uniform rate of convergence and the nonstandard limiting distribution of the nonparametric threshold estimator. We also obtain the root-n consistency and the asymptotic normality of the regression coefficient estimator. We illustrate empirical relevance of this new model by estimating the tipping point in social segregation problems as a function of demographic characteristics; and determining metropolitan area boundaries using nighttime light intensity collected from satellite imagery.

Quantum Error Correction: Noise-Adapted Techniques and Applications

The quantum computing devices of today have tens to hundreds of qubits that are highly susceptible to noise due to unwanted interactions with their environment. The theory of quantum error correction provides a scheme by which the effects of such noise on quantum states can be mitigated, paving the way for realising robust, scalable quantum computers. In this article we survey the current landscape of quantum error correcting (QEC) codes, focusing on recent theoretical advances in the domain of noise-adapted QEC, and highlighting some key open questions. We also discuss the interesting connections that have emerged between such adaptive QEC techniques and fundamental physics, especially in the areas of many-body physics and cosmology. We conclude with a brief review of the theory of quantum fault tolerance which gives a quantitative estimate of the physical noise threshold below which error-resilient quantum computation is possible.