Reliable Method For Estimation Research Articles

Calibration and Evaluation of Alternative Methods for Reliable Estimation of Reference Evapotranspiration in South Korea

Calibration and Evaluation of Alternative Methods for Reliable Estimation of Reference Evapotranspiration in South Korea

Establishing legal threshold of 18-years based on the assessment of mandibular molars using three different methods - An observational study.

The study evaluates the feasibility of employing the radiographic visibility of the root pulp and periodontal ligament in mandibular molars for age estimation, particularly focusing on the 18 years of age threshold. This study additionally investigates the potential of root canal width reduction in mandibular molars, as a reliable method for forensic age estimation in living individuals. A cross-sectional study was conducted to assess the radiographic visibility of the root pulp (RPV) and the root canal width (RCW) of mandibular first, second, and third molars along with the radiographic visibility of the periodontal ligament (PLV) of mandibular third molars, in a sample of 403 individuals aged 16-25 years (220 males and 183 females). Data regarding age for different stages of RPV and PLV and various types of RCW were recorded and observed for sex-based differences. Results obtained were tabulated and descriptive statistics were applied to summarise the findings. Individuals over 18 years old were classified with higher accuracy using stage 3 of the RPV scoring system in all mandibular molars (first, second, and third) compared to stage 2, which was also effective for the second and third molars. This result held regardless of sex and side examined. Additionally, root canal width (RCW) assessment demonstrated that individuals with RCW types A, B, and C were more likely to be under 18 years old in both sexes. Conversely, individuals with RCW type U on the right side for males and the left side for females exhibited a higher likelihood of being above 18 years old. The study suggests that the assessment of mandibular molars could potentially serve as an auxiliary tool in age estimation methods, particularly for approximating individuals around the 18 years of age threshold. Further investigation is warranted to explore the potential application of root canal width measurements in forensic age estimation.

STATISTICAL INFERENCE ON SINE-EXPONENTIAL DISTRIBUTION PARAMETER

The Sine-Exponential (Sine-E) distribution is a probability distribution that combines the periodic behavior of the sine function with the decay characteristic of the exponential function. This study addresses the problem of identifying the most accurate and reliable estimation method for the parameter of the Sine-E distribution. The objective is to evaluate various parameter estimation techniques, including Maximum Likelihood Estimation (MLE), Least Squares Estimation (LSE), Weighted Least Squares Estimation (WLSE), Maximum Product of Spacing Estimation (MPSE), Cramer-von-Mises Estimation (CVME), and Anderson-Darling Estimation (ADE), using Mean Square Error (MSE) as the criterion for determining the technique with the minimum error. The study’s findings reveal that as sample size increases, the parameter estimates for all techniques converge to the true parameter value, with decreases in bias, MSE, and mean relative estimates. Among the techniques evaluated, the MPSE method consistently provides estimates closest to the true parameter value and exhibits the least bias and lowest MSE across small, moderate, and large sample sizes, making it the best estimator for the Sine-E distribution.

Contrastive fine-grained domain adaptation network for EEG-based vigilance estimation

Vigilance state is crucial for the effective performance of users in brain-computer interface (BCI) systems. Most vigilance estimation methods rely on a large amount of labeled data to train a satisfactory model for the specific subject, which limits the practical application of the methods. This study aimed to build a reliable vigilance estimation method using a small amount of unlabeled calibration data. We conducted a vigilance experiment in the designed BCI-based cursor-control task. Electroencephalogram (EEG) signals of eighteen participants were recorded in two sessions on two different days. And, we proposed a contrastive fine-grained domain adaptation network (CFGDAN) for vigilance estimation. Here, an adaptive graph convolution network (GCN) was built to project the EEG data of different domains into a common space. The fine-grained feature alignment mechanism was designed to weight and align the feature distributions across domains at the EEG channel level, and the contrastive information preservation module was developed to preserve the useful target-specific information during the feature alignment. The experimental results show that the proposed CFGDAN outperforms the compared methods in our BCI vigilance dataset and SEED-VIG dataset. Moreover, the visualization results demonstrate the efficacy of the designed feature alignment mechanisms. These results indicate the effectiveness of our method for vigilance estimation. Our study is helpful for reducing calibration efforts and promoting the practical application potential of vigilance estimation methods.

Incorporating Honey Badger Algorithm in Estimating Gamma Distribution With Application to Stock Price Modelling

This study evaluates the performance of various estimation methods in stock price analysis across diverse parameters, focusing on the Honey Badger Algorithm (HBA). The purpose is to determine the most accurate and reliable method for parameter estimation. Methodologically, we analyze data spanning eight years from publicly traded Malaysian property companies, employing financial metrics such as Mean Absolute Error (MAE) and Root Mean Square Error (RMSE). Our findings highlight HBA’s consistent precision in parameter estimation, with values closely aligning with initial parameters across different stock sizes. For example, HBA-Gamma model achieves an MAE of 0.0592 and an RMSE of 0.8458 for 13 stocks, demonstrating its proficiency in capturing stock price distributions in dynamic markets. In contrast, the Artificial Immune System (AIS) provides reasonable estimates but with higher variability. The Regression Method exhibits mixed outcomes, displaying accuracy in some cases but notable variability and reduced precision, especially with larger datasets. The Moment Method, while adequate, shows slightly higher variance compared to both HBA and AIS. Further analysis using Log Likelihood values confirms HBA’s superior fit to the data, consistently surpassing AIS, Regression Method, and Moment Method in likelihood maximization across various stock numbers. Specifically, HBA exhibits lower MAE and RMSE values of 0.1034 and 0.06723, respectively, for 26 stocks, further validating its effectiveness in parameter estimation and stock price prediction. These findings underscore the importance of integrated approaches that account for market nuances rather than relying solely on individual model forecasts. The results affirm HBA’s potential for informed investment decision-making, emphasizing its robust performance and enhanced predictive capabilities compared to alternative methodologies. However, further research is needed to assess the generalizability of these findings to other markets and contexts.

Intervention and adaptation options for measuring brand trust in the context of its dimensionality with an emphasis on the generational context

Objective: This article aims to analyse the model of perception of trust in the selectedbrand (Subway) with the help of the modified tool “Perceived Brand Trust”, and to investigatethe difference in generational perception of trust in the investigated brand.Methodology: In this article, we use statistical methods such as elements of descriptive statisticsand inductive statistics with an emphasis on confirmatory factor analysis, reliabilityestimation methods, and one-way ANOVA.Results: The result is a modification of the three-dimensional brand trust perception modeland a demonstration of its use in practice.Limitations: Limitations can be observed in self-collection and the use of respondents’personal reflection in the context of brand trust.Practical implications: The article has academic, theoretical and practical benefits. Thepractical benefit can be seen in the creation and verification of a model for measuringbrand trust perception, which can be applied to any brand.

Sampling and active learning methods for network reliability estimation using K-terminal spanning tree

Network reliability analysis remains a challenge due to the increasing size and complexity of networks. This paper presents a novel sampling method and an active learning method for efficient and accurate network reliability estimation under node failure and edge failure scenarios. The proposed sampling method adopts Monte Carlo technique to sample component lifetimes and the K-terminal spanning tree algorithm to accelerate structure function computation. Unlike existing methods that compute only one structure function value per sample, our method generates multiple component state vectors and corresponding structure function values from each sample. Network reliability is estimated based on survival signatures derived from these values. A transformation technique extends this method to handle both node failure and edge failure. To enhance efficiency of proposed sampling method and achieve adaptability to network topology changes, we introduce an active learning method utilizing a random forest (RF) classifier. This classifier directly predicts structure function values, integrates network behaviors across diverse topologies, and undergoes iterative refinement to enhance predictive accuracy. Importantly, the trained RF classifier can directly predict reliability for variant networks, a capability beyond the sampling method alone. Through investigating several network examples and two practical applications, the effectiveness of both proposed methods is demonstrated.

A Reliable DBH Estimation Method Using Terrestrial LiDAR Points through Polar Coordinate Transformation and Progressive Outlier Removal

A Reliable DBH Estimation Method Using Terrestrial LiDAR Points through Polar Coordinate Transformation and Progressive Outlier Removal

A non-destructive, low cost and high throughput colorimetric method for chlorophyll estimation in rice (Oryza sativa L.)

Leaf chlorophyll is an important biochemical parameter used to assess plant health under stress. Chlorophyll is invariably estimated using destructive method of acetone or ethanol extraction. Reflectance spectroscopy such as IR, VIS–NIR, combined with chemometric, has been widely used in plant leaf chemical analysis. Here we report a cheap and reliable spectroscopic method of chlorophyll estimation using a low-cost handheld spectrometer. We standardized the method in a rice diversity panel of 264 genotypes using L*, a* and b* parameters using a randomly taken calibration and validation sample. The parameters used for fitting the regression analysis were L*, a*, b* and δ E that indicates deviation of L*, a* and b* values of sample from the chlorophyll solution of a known concentration. We fitted the regression of total chlorophyll in calibration sample with L*, a*, b* and δ E separately as well as multiple regression with all parameters. The best R2 value (0.671) was observed for a* and the lowest for L* (0.436). Using multiple regression, the R2 value increased to 0.778 (p < 0.005). We used the regression equation for validation sample and obtained R2 value of 0.724 indicating reliable explanatory potential of variables. The parametric test for model reliability indicates good model fit of the observed relationship between chlorophyll content and L*, a*, b* and δ E. The method is cost effective, non-destructive and takes less time (< 10 s) and can be conveniently used for screening large diversity panels especially in case of repeated measurements across growth stages under stress.

Age Estimation of Children and Young Adults of Jharkhand Using Mineralization of Third Molars and Its Relation to Chronological Age: A Retrospective Analysis.

Background Dental age estimation plays an enormous role in the determination of an individual's identity and age in forensic and anthropological fields. The estimation of the chronological age of the individual is also importantin the diagnosis, treatment planning, and treatment outcomes in the dental field. The third molar has some inimitable characteristics in terms of its size, shape, formation, and long path of eruption and usually erupts after puberty, which seems to be a reliable method of age estimation in adulthood. To establish the individual's identity, inference of age has gained considerable attention in forensics, and the aspect of dentistry has broadened nowadays. Thus the present study was conducted. Methodology The digital orthopantomograms of 720 patients who were exposed to X-rays for routine examinationwere assessed, and calcification of the tooth was observed. In order to ensure the blinding of the examiners, radiographs were numerically coded. Clinical stages of the tooth were categorised into erupted, pre-erupted, and missing. Statistical analysis was performed by IBM SPSS Statistics for Windows, Version 25.0 (IBM Corp., Armonk, NY), with a level of significance set below 5%. Results The age of the patients whoseOPGs were assessed ranged from 6 to 22 years, with a mean age of 18.93±3.129 years. Among the 720 participants, 370 (51.4%) were male and 350 (48.6%) were female. When the clinical status of the third molar among all the participants was assessed, in 148 (20.6%) subjects, third molars had erupted; in 188 (26.1%) subjects, the third molars were in the pre-erupted stage; and in 384 (53.30%), third molars were missing. When comparing the clinical status of the third molar in both arches and between genders, it was found that missing molars were common infemales and the mandible arch, with statistically significant p-values. A comparison of Demirjian's stages between genders showed that the mean age to attain stage H was 21.37±0.774 yearsamong males and 21.69±0.616 years among females. This means that the calcification of third-molar attainment occurs earlier in malescompared with females. In a similar comparison between the upper and lower arches, it was found that calcification of the third molar was attained earlier in the maxillary arch compared to the mandibular arch. Conclusion It was concluded that the third molar is a versatile tooth and its path of mineralization can be used in orthodontics, pedodontics, and forensics to estimate chronological age, and chronological age significantly follows Demirjian's stages of third molar calcification. Third molar calcification occurred earlier in the maxillary arch and males, whereas several impacted molars were higher in females.

Experimental measurement of local noise power spectrum (NPS) in photon counting detector-CT (PCD-CT) using a single data acquisition.

Accurate noise power spectra (NPS) measurement in clinical X-ray CT exams is challenging due to the need for repeated scans, which expose patients to high radiation risks. A reliable method for single CT acquisition NPS estimation is thus highly desirable. To develop a method for estimating local NPS from a single photon counting detector-CT (PCD-CT)acquisition. A novel nearly statistical bias-free estimator was constructed from the raw counts data of PCD-CT scan to estimate the variance of sinogram projection data. An analytical algorithm is employed to reconstruct point-wise covariance between any two image pixel/voxel locations and . A Fourier transform is applied to obtain the desired point-wise NPS for any chosen location . The method was validated using experimental data acquired from a benchtop PCD-CT system with various physical phantoms, and the results were compared with the conventional local NPS measurement method using repeated scans and statistical ensembleaveraging. The experimental results demonstrate that (1) the proposed method can achieve pointwise/local NPS measurement for a region of interest (ROI) located at any chosen position, accurately characterizing the NPS with spatial structures resulting from image content heterogeneity; (2) the local NPS measured using the proposed method show a higher precision in the measured NPS compared to the conventional measurement method; (3) spatial averaging of the local NPS yields the conventional NPS for a given localROI. A new method was developed to enable local NPS from a single PCD-CTacquisition.

Cerebral hemodynamics and optic nerve sheath diameter acquired via neurosonology in critical patients with severe coronavirus disease: experience of a national referral hospital in Peru.

We aimed to describe the neurosonological findings related to cerebral hemodynamics acquired using transcranial Doppler and to determine the frequency of elevated ICP by optic nerve sheath diameter (ONSD) measurement in patients with severe coronavirus disease (COVID-19) hospitalized in the intensive care unit of a national referral hospital in Peru. We included a retrospective cohort of adult patients hospitalized with severe COVID-19 and acute respiratory failure within the first 7 days of mechanical ventilation under deep sedoanalgesia, with or without neuromuscular blockade who underwent ocular ultrasound and transcranial Doppler. We determine the frequency of elevated ICP by measuring the diameter of the optic nerve sheath, choosing as best cut-off value a diameter equal to or >5.8 mm. We also determine the frequency of sonographic patterns obtained by transcranial Doppler. Through insonation of the middle cerebral artery. Likewise, we evaluated the associations of clinical, mechanical ventilator, and arterial blood gas variables with ONSD ≥5.8 mm and pulsatility index (PI) ≥1.1. We also evaluated the associations of hemodynamic findings and ONSD with mortality the effect size was estimated using Poisson regression models with robust variance. This study included 142 patients. The mean age was 51.39 ± 13.3 years, and 78.9% of patients were male. Vasopressors were used in 45.1% of patients, and mean arterial pressure was 81.87 ± 10.64 mmHg. The mean partial pressure of carbon dioxide (PaCO2) was elevated (54.08 ± 16.01 mmHg). Elevated intracranial pressure was seen in 83.1% of patients, as estimated based on ONSD ≥5.8 mm. A mortality rate of 16.2% was reported. In the multivariate analysis, age was associated with elevated ONSD (risk ratio [RR] = 1.07). PaCO2 was a protective factor (RR = 0.64) in the cases of PI ≥ 1.1. In the mortality analysis, the mean velocity was a risk factor for mortality (RR = 1.15). A high rate of intracranial hypertension was reported, with ONSD measurement being the most reliable method for estimation. The increase in ICP measured by ONSD in patients with severe COVID-19 on mechanical ventilation is not associated to hypercapnia or elevated intrathoracic pressures derived from protective mechanical ventilation.

Monte Carlo simulation studies of reliability in psychometrics

Monte Carlo simulation studies are widely used in reliability research. This study reviewed 85 published Monte Carlo simulation studies investigating reliability. The review focused on the prevalence of particular reliability estimation methods and estimators, as well as adherence to previous recommendations for the Monte Carlo simulation method. It appears researchers do not fully adhere to these recommendations. Most of the reviewed studies have limitations in at least one of the following: reporting on the data generation procedure, selection of the number of replications, selection of conditions, benchmark utilization, and performance evaluation. Findings also suggest internal consistency in general and coefficient α are the most prevalent. Conversely, some reliability estimation methods and estimators that can be useful under many empirical conditions appear to be mostly overlooked. In the case of internal consistency, these are relatively obscure forms of α, λ2, λ4, μ-series, Kristof's coefficient, Feldt-Gilmer coefficient, maximal reliability, greatest lower bound to reliability, ω family, structural equation modeling-based coefficients, and internal consistency confidence intervals. Overlooked reliability estimation methods are parallel forms, test-retest, multilevel reliability, latent class-based reliability, reliability of an individual, and Bayesian reliability. Suggestions for future research have been offered.

Travel Time Reliability Estimation in Urban Road Networks: Utilization of Statistics Distribution and Tensor Decomposition

The travel time reliability (TTR) is crucial for evaluating the reliability of road networks, but real traffic data is often incomplete and sparse. This study validates that road network TTR conforms to a normal distribution and devises a quantification approach for road network TTR. Two reliability estimation methods are tailored for two data sources: section detectors and mobile detectors. Simulation experiments have confirmed the effectiveness of these methods. The study emphasizes that the TTR estimation method using traffic section data (S-TTR), which is based on the verified normal distribution assumption, maintains average absolute errors below 10%. On the other hand, the TTR estimation method that utilizes sparse trajectory data (T-TTR), which relies on tensor decomposition, proficiently fills in all missing data with an average error of 0.0059.

Comparison of Different Methods for Ancient Ship Calm Water Resistance Estimation

The remains of ancient ships from various time periods are commonly found on land and under the sea in conditions that make it difficult to reconstruct their original form and structure. For this reason, the reconstruction should be supported by other data, such as data on similar ships, but also by certain assumptions. The results of the reconstruction are significant not only in a historical sense but are of exceptional importance when building floating replicas. Two ships, Nin 1 and Nin 2, today for promotional purposes known as Condurae Croaticae, were found in Nin (Croatia) at the end of the 1960s. They are about 8 to 10 m long, and tentatively dated to the 11th century AD, although there are indications that they could be dated two centuries later. Based on archaeological finds exhibited in the Museum of Nin Antiquities, hull line drawings were created, according to which two floating replicas were made at the end of the 1990s. Considering the problem of hogging that appeared in both ships, a new proposal for the reconstruction of the original hull lines was performed based on the available documentation. The aim of this paper is a systematic analysis of its calm water resistance. Based on the established credibility of experimental testing, a scale model (1:4 ratio) of the Nin 1 vessel is constructed and evaluated through towing tank experiments. The second approach, the CFD method, is a reliable numerical method for calm resistance estimation, but it is rarely used in the analysis of ancient ships. Finally, the widely used empirical Holtrop method is also applied, but it was developed for ships of larger dimensions and with large parts of flat bottoms and, therefore, the more appropriate Delft Hull Yacht Series method is also tested. The results obtained by applying the four mentioned methods are compared and discussed.

Fitting pseudo-Sérsic (Spergel) light profiles to galaxies in interferometric data: The excellence of the uυ-plane

Modern (sub)millimeter interferometers, such as ALMA and NOEMA, offer high angular resolution and unprecedented sensitivity. This provides the possibility to characterize the morphology of the gas and dust in distant galaxies. To assess the capabilities of the current software in recovering morphologies and surface brightness profiles in interferometric observations, we tested the performance of the Spergel model for fitting in the uυ-plane, which has been recently implemented in the IRAM software GILDAS (uv_fit). Spergel profiles provide an alternative to the Sérsic profile, with the advantage of having an analytical Fourier transform, making them ideal for modeling visibilities in the uυ-plane. We provide an approximate conversion between the Spergel index and the Sérsic index, which depends on the ratio of the galaxy size to the angular resolution of the data. We show through extensive simulations that Spergel modeling in the uυ-plane is a more reliable method for parameter estimation than modeling in the image plane, as it returns parameters that are less affected by systematic biases and results in a higher effective signal-to-noise ratio. The better performance in the uυ-plane is likely driven by the difficulty of accounting for a correlated signal in interferometric images. Even in the uυ-plane, the integrated source flux needs to be at least 50 times larger than the noise per beam to enable a reasonably good measurement of a Spergel index. We characterized the performance of Spergel model fitting in detail by showing that parameter biases are generally low (&lt;10%) and that uncertainties returned by uv_fit are reliable within a factor of two. Finally, we showcase the power of Spergel fitting by reexamining two claims of extended halos around galaxies from the literature, showing that galaxies and halos can be successfully fitted simultaneously with a single Spergel model.

Assessment of the estimation methods for the normal boiling point of liquid organic hydrogen carriers

Liquid organic hydrogen carrier (LOHC) presents a promising solution for hydrogen storage. However, its development has been impeded by the absence of normal boiling point (NBP) data for hydrogenation products, especially saturated alicyclic compounds. This gap spurs the search for a reliable and convenient estimation method to aid in the screening of new mediums and the design of chemical processes. Thanks to the intrinsic simplicity, 17 group contribution models were selected and evaluated to identify the optimal ones for different types of alicyclic compounds. The best-performing model was subsequently refined. Furthermore, two models tailored for predicting the NBP of saturated alicyclic compounds were proposed using classical approaches and artificial neural networks. The results indicate that the GCN and GM models yield lower errors in estimating the NBP of alicyclic hydrocarbons, while the GIC2 model performs better for heterocyclic compounds. The developed models are more accurate compared to the existing models. Notably, the neural-network-based model exhibits excellent performance. These models are expected to provide useful insights for large-scale screening of LOHCs for hydrogen storage.

Evaluating legal age of 18 years through observation of third molars using Gambier et al. method in an orthopantomographic sample of subadults from South India

In forensic practice, medicolegal physicians are often tasked with estimating age using dental evidence. This calls for an uncomplicated, reliable, and reproducible method for dental age estimation, enabling physicians to proceed without specific odontological expertise. Among various dental methods, third molar eruption analyses are less complicated and easier to perform. In our study, we explored the effectiveness of Gambier et al.'s scoring system, which examines the eruption of all third molars. We retrospectively analysed 1032 orthopantomograms (528 males and 504 females) of individuals aged between 15 and 24 years. The mean chronological age increased with the progression of stages (1 to 3) and phases (A to D) of the third molar eruption for both sexes. In terms of stages, none showed significant discrimination between minors (<18 years) and adults (>18 years), especially for males. However, Gambier’s phase D displayed a relatively high likelihood of being 18 years or older, with an overall 85.9 % of males and 95.7 % of females having all third molars in stage 3 being 18 years or older. While the tested method could be helpful in indicating the completion of the 18th year of life, caution is advised (due to a high percentage of false positives), and it should be used alongside other age assessment methods by experts.

A reliability estimation method based on combination of failure mechanism and ANN supported wiener processes

For some engineering application, accurately estimating reliability only depend on the history data or failure mechanism is difficult to implement, due to the lack of data and imperfect theory of failure mechanism. Namely, both history data and failure mechanism should be utilized to improve the reliability estimation accuracy for engineering applications. Hence, we construct a reliability estimation method by fusing the failure mechanism and artificial neural network (ANN) supported Wiener processes for utilizing both history data and failure mechanism. ANN and failure mechanism are integrated into Wiener process with random effects, respectively. Bayesian model averaging (BMA) method is adapted to combine the failure mechanism with ANN supported Wiener processes, as well as to update the model parameters by fusing data. Based on a typical aviation hydraulic pump's actual dataset, we illustrate the advantages of our approach by comparing to Wiener process supported only by ANN or failure mechanism in engineering practices. The proposed method shows superiorities on reliability estimation considering the estimation accuracies comparing the other two models.

Testing a novel sensor design to jointly measure cosmic-ray neutrons, muons and gamma rays for non-invasive soil moisture estimation

Abstract. Cosmic-ray neutron sensing (CRNS) has emerged as a reliable method for soil moisture and snow estimation. However, the applicability of this method beyond research has been limited due to, among others, the use of relatively large and expensive sensors. This paper presents the tests conducted on a new scintillator-based sensor especially designed to jointly measure neutron counts, muons and total gamma rays. The neutron signal is first compared against two conventional gas-tube-based CRNS sensors at two locations. The estimated soil moisture is further assessed at four agricultural sites, based on gravimetric soil moisture collected within the sensor footprint. Muon fluxes are compared to the incoming neutron variability measured at a neutron monitoring station and total gammas counts are compared to the signal detected by a gamma ray spectrometer. The results show that the neutron dynamic detected by the new scintillator-based CRNS sensor is well in agreement with conventional CRNS sensors. The derived soil moisture also agreed well with the gravimetric soil moisture measurements. The muons and the total gamma rays simultaneously detected by the sensor show promising features to account for the incoming variability and for discriminating irrigation and precipitation events, respectively. Further experiments and analyses should be conducted, however, to better understand the accuracy and the added value of these additional data for soil moisture estimation. Overall, the new scintillator design shows to be a valid and compact alternative to conventional CRNS sensors for non-invasive soil moisture monitoring and to open the path to a wide range of applications.