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Symmetry ◽  
2022 ◽  
Vol 14 (1) ◽  
pp. 122
Author(s):  
Anam Iqbal ◽  
Tahir Mahmood ◽  
Zulfiqar Ali ◽  
Muhammad Riaz

Innovations in technology assist the manufacturing processes in producing high-quality products and, hence, become a greater challenge for quality engineers. Control charts are frequently used to examine production operations and maintain product quality. The traditional charting structures rely on a response variable and do not incorporate any auxiliary data. To resolve this issue, one popular approach is to design charts based on a linear regression model, usually when the response variable shows a symmetric pattern (i.e., normality). The present work intends to propose new generalized linear model (GLM)-based homogeneously weighted moving average (HWMA) and double homogeneously weighted moving average (DHWMA) charting schemes to monitor count processes employing the deviance residuals (DRs) and standardized residuals (SRs) of the Poisson regression model. The symmetric limits of HWMA and DHWMA structures are derived, as SR and DR statistics showed a symmetric pattern. The performance of proposed and established methods (i.e., EWMA charts) is assessed by using run-length characteristics. The results revealed that SR-based schemes have relatively better performance as compared to DR-based schemes. In particular, the proposed SR-DHWMA chart outperforms the other two, namely SR-EWMA and SR-HWMA charts, in detecting shifts. To illustrate the practical features of the study’s proposal, a real application connected to the additive manufacturing process is offered.


MAUSAM ◽  
2021 ◽  
Vol 67 (4) ◽  
pp. 841-848
Author(s):  
ENAKSHI SAHA ◽  
ARNAB HAZRA ◽  
PABITRA BANIK

The SARIMA time series model is fitted to the monthly average maximum and minimum temperature data sets collected at Giridih, India for the years 1990-2011. From the time-series  plots, we observe that the patterns of both the series are quite different; maximum temperature series contain sharp peaks in almost all the years while it is not true for the minimum temperature series and hence both the series are modeled separately (also for the sake of simplicity). SARIMA models are selected based on observing autocorrelation function (ACF) and partial autocorrelation function (PACF) of the monthly temperature series. The model parameters are obtained by using maximum likelihood method with the help of three tests [i.e., standard error, ACF and PACF of residuals and Akaike Information Criteria (AIC), Bayesian Information Criteria (BIC) and corrected Akaike Information Criteria (AICc)]. Adequacy of the selected models is determined using diagnostic checking with the standardized residuals, ACF of residuals, normal Q-Q plot of the standardized residuals and p-values of the Ljung-Box statistic. The models ARIMA (1; 0; 2) × (0; 1; 1)12  and ARIMA (0; 1; 1) × (1; 1; 1)12  are finally selected for forecasting of monthly average maximum and minimum temperature values respectively for the eastern plateau region of India.  


2021 ◽  
Vol 15 (11) ◽  
pp. 3084-3086
Author(s):  
Ali Akram ◽  
Kaleemullah Qaisrani ◽  
Nadeem Ullah

Background: COVID-19 is a wide spreading disease starts from Wuhan a city of China in east. Earlier symptoms include fever, cough and fatigue later on patients may present with loss of smell and taste, sore throat, nasal congestion and muscle or joint pain. Its long term effects may include respiratory distress and neurological symptoms. Aim: To determine the frequency of different symptoms in patients with COVID-19 presenting at outpatients department of Nishtar Hospital Multan. Methodology: This cross sectional study was conducted at department of medicine, Nishtar Medical University, Multan, from September 2020 to September 2021. This study was carried out on 200 patients presenting with symptoms of COVID-19 and diagnosis was confirmed after admission. Main variables of study were symptoms of COVID-19 like cough, fever, running nose, breathlessness, headache and palpitations. SPSS version 22 was used for data analysis. Results: Majority of the patients were (60.0%) between age group 46-60 years. The most common symptoms were fever and cough, (79.0%) and (65.0%), respectively. The symptoms recorded between both male and female were almost equal, (standardized residuals<1.96 and p>0.05). But, fever and running nose were most common among the females, (p=0.028) and (p=0.050), respectively. Conclusion: COVID-19 presents with variety of symptoms and fever and cough were most common among these symptoms. COVID-19 positive patients can be present asymptomatically. All persons who come into contact with COVID19 patients should be go through the PCR lab test. Keywords: Novel COVID 19, Acute Respiratory Distress Syndrome, Contagious, Pandemic


2021 ◽  
Vol 21 (S2) ◽  
Author(s):  
Jorge Bravo ◽  
Hugo Rosado ◽  
Pablo Tomas-Carus ◽  
Cristina Carrasco ◽  
Nuno Batalha ◽  
...  

Abstract Background Fall risk assessment in older people is of major importance for providing adequate preventive measures. Current predictive models are mainly focused on intrinsic risk factors and do not adjust for contextual exposure. The validity and utility of continuous risk scores have already been demonstrated in clinical practice in several diseases. In this study, we aimed to develop and validate an intrinsic-exposure continuous fall risk score (cFRs) for community-dwelling older people through standardized residuals. Methods Self-reported falls in the last year were recorded from 504 older persons (391 women: age 73.1 ± 6.5 years; 113 men: age 74.0 ± 6.1 years). Participants were categorized as occasional fallers (falls ≤1) or recurrent fallers (≥ 2 falls). The cFRs was derived for each participant by summing the standardized residuals (Z-scores) of the intrinsic fall risk factors and exposure factors. Receiver operating characteristic (ROC) analysis was used to determine the accuracy of the cFRs for identifying recurrent fallers. Results The cFRs varied according to the number of reported falls; it was lowest in the group with no falls (− 1.66 ± 2.59), higher in the group with one fall (0.05 ± 3.13, p < 0.001), and highest in the group with recurrent fallers (2.82 ± 3.94, p < 0.001). The cFRs cutoff level yielding the maximal sensitivity and specificity for identifying recurrent fallers was 1.14, with an area under the ROC curve of 0.790 (95% confidence interval: 0.746–0.833; p < 0.001). Conclusions The cFRs was shown to be a valid dynamic multifactorial fall risk assessment tool for epidemiological analyses and clinical practice. Moreover, the potential for the cFRs to become a widely used approach regarding fall prevention in community-dwelling older people was demonstrated, since it involves a holistic intrinsic-exposure approach to the phenomena. Further investigation is required to validate the cFRs with other samples since it is a sample-specific tool.


Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Lorena-De Arriba-Rodríguez ◽  
Francisco Ortega-Fernández ◽  
Joaquín M. Villanueva-Balsera ◽  
Vicente Rodríguez-Montequín

Corrosion is one of the main concerns in the field of structural engineering due to its effect on steel buried in soil. Currently, there is no clearly established method that allows its calculation with precision and ensures the durability of this type of structures. Qualitative methods are commonly used rather than quantitative methods. The objective of this research is the development of a multivariate quantitative predictive model for estimating the loss of thickness that will occur in buried hot-dip galvanized steel as a function of time. The technique used in the modelling is the Adaptive Regression of Multivariate Splines (MARS). The main drawback of this kind of studies is the lack of data since it is not possible to have a priori the corrosive behaviour that the buried material will have as a function of time. To solve this issue, a solid and reliable database was built from the analysis and treatment of the existing literature and with the results obtained from a predictive model to estimate the thickness loss of ungalvanized steel. The input variables of the model are 5 characteristics of the soil, the useful life of the structure, and the loss of corroded ungalvanized steel in the soil. This last data is the output variable of another previous predictive model to estimate the loss of thickness of bare steel in a soil. The objective variable of the model is the loss of thickness that hot-dip galvanized steel will experience buried in the ground and expressed in g/m2. To evaluate the performance and applicability of the proposed model, the statistical metrics RMSE, R2, MAE, and RAE and the graphs of standardized residuals were used. The results indicated that the model offers a very high prediction performance. Specifically, the mean square error was 290.6 g/m2 (range of the objective variable is from 51.787 g/m2 to 5950.5 g/m2), R2 was 0.96, and from a relative error of 0.14, the success of the estimate was 100%. Therefore, the use of the proposed predictive model optimizes the relationship between the amount of hot-dip galvanized steel and the useful life of the buried metal structure.


2021 ◽  
Vol 13 (16) ◽  
pp. 9339
Author(s):  
Elżbieta Jasińska ◽  
Edward Preweda

The analysis of a city’s spatial development, in terms of a location that meets the needs of its inhabitants, requires many approaches. The preliminary assessment of the collected material showed that there was real estate in the database whose price did not have market characteristics. For the correct formulation of the valuation model, it is necessary to detect and eliminate or reduce the impact of these properties on the valuation results. In this study, multivariate analysis was used and three methods of detecting outliers were verified. The database of 8812 residential premises traded on the primary market in Kraków was analyzed. In order to detect outliers, the following indices were determined: projection matrix, Mahalanobis distances, standardized chi test and Cook distances. Critical values were calculated based on the formulas proposed in the publication. The probability level was P = 0.95. The article shows that the selected methods of eliminating outliers—the methods of standardized residuals and the Cook’s distance method give similar regression models. Further analysis (with the use of classification tree methods) made it possible to distinguish zones that are homogeneous in terms of price dispersion. In these zones, a set of features influencing real estate prices were determined.


Author(s):  
Kaigang Li ◽  
Denise L. Haynie ◽  
Xiang Gao ◽  
Leah M. Lipsky ◽  
Tonja Nansel ◽  
...  

Abstract Objectives We validated a continuous cardiometabolic risk (CMR) measure among adolescents. Methods Five metabolic syndrome (MetS) components including waist circumference, triglycerides, high-density lipoprotein cholesterol, fasting blood glucose, and mean arterial pressure were assessed in a national cohort of U.S. adolescents (n=560; 16.5 ± 0.5 y/o at baseline) in 10th grade (2010, Wave 1 (W1)), and follow-up assessments four (W4) and seven (W7) years later. Separately by wave, linear regressions were fitted to each MetS component controlling for age, sex, and race/ethnicity, and yielded standardized residuals (Z-scores). Wave-specific component Z-scores were summed to obtain composite CMR Z-scores. Four- and seven-year CMR change (CMR-diff W1–W4 and W1–W7). and average CMR risk (CMR-avg; (W1 + W4)/2 and (W1 + W7)/2) were calculated using the CMR Z-scores. W7 MetS was determined using adult criteria. Student’s t-test and receiver operating characteristic (ROC) curve were conducted. Results Participants meeting the adult criteria for MetS at W7 (74 of 416, 17.8%) had statistically significant (p<0.01) higher values for W1 CMR Z-scores (0.92 vs. −0.21), W4 CMR Z-scores (1.69 vs. −0.28), W7 CMR Z-scores (2.21 vs. −0.55), W1–W4 CMR-avg (1.53 vs. −0.27), W1–W7 CMR-diff (1.29 vs. −0.21), and W1–W7 CMR-avg (1.46 vs. −0.48) than those not meeting MetS criteria. Most results were similar for males and females in the sex-stratified analyses. The areas under the ROC curve were 0.61, 0.71, and 0.75 for W1, W4 and W7 Z-scores. Conclusions Findings support the validity of the continuous CMR Z-scores calculated using linear regression in evaluating and monitoring CMR profiles from adolescence to early adulthood.


2021 ◽  
Vol 3 ◽  
Author(s):  
Nuno Leite ◽  
Jorge Arede ◽  
Ximing Shang ◽  
Julio Calleja-González ◽  
Alberto Lorenzo

The aims of this study were two-fold: (1) to inspect separately for the relative age and birthplace effects for players selected in the National Basketball Association (NBA) draft; (2) to explore the interaction among these factors and analyse this interaction in players' career performance. The database was obtained from the official records of the players (n = 1,738), who were selected during the annual editions of the NBA Draft from 1990 to 2019. The participants' date of birth was analyzed according to the month of birth and divided into four quartiles. The place of birth was compared to the distribution of the general population' places of birth based on different communities' sizes. Chi-square analysis were used to determine if the relative age and birthplace of the players drafted differed in any systematic way from official census population distributions. Cluster analysis and standardized residuals were calculated to analyse the interaction among the contextual factors and the players' career performance. The data revealed that early-born players (Q1 and Q2) were over-represented. Moreover, players born in smaller cities (&lt;100,000) were over-represented. The interaction analysis revealed that the players born in the bigger communities relate mainly with relatively younger players, and clusters that correspond to players born in smaller communities integrated the relatively older players. No differences were found in the players' career performance. Researchers, coaches and practitioners should be aware of the interaction between contextual factors to help nurture the development of sport talent regardless of age-related issues or communities' size.


2021 ◽  
Vol 12 ◽  
Author(s):  
Darko Stefanovski ◽  
Naresh M. Punjabi ◽  
Raymond C. Boston ◽  
Richard M. Watanabe

Glucose and free fatty acids (FFA) are essential nutrients that are both partly regulated by insulin. Impaired insulin secretion and insulin resistance are hallmarks of aberrant glucose disposal, and type 2 diabetes (T2DM). In the current study, a novel model of FFA kinetics is proposed to estimate the role insulin action on FFA lipolysis and oxidation allowing estimation of adipose tissue insulin sensitivity (SIFFA). Twenty-five normal volunteers were recruited for the current study. To participate, volunteers had to be less than 40 years of age and have a body mass index (BMI) &lt; 30 kg/m2, and be free of medical comorbidity. The proposed model of FFA kinetics was used to analyze the data derived from the insulin-modified FSIGT. Mean fractional standard deviations of the parameter estimates were all less than 20%. Standardized residuals of the fit of the model to the FFA temporal data were randomly distributed, with only one estimated point lying outside the 2-standard deviation range, suggesting an acceptable fit of the model to the FFA data. The current study describes a novel one-compartment non-linear model of FFA kinetics during an FSIGT that provides an FFA metabolism insulin sensitivity parameter (SIFFA). Furthermore, the models suggest a new role of glucose as the modulator of FFA disposal. Estimates of SIFFA confirmed previous findings that FFA metabolism is more sensitive to changes in insulin than glucose metabolism. Novel derived indices of insulin sensitivity of FFA (SIFFA) were correlated with minimal model indices. These associations suggest a cooperative rather than competitive interplay between the two primary nutrients (glucose and FFA) and allude to the FFA acting as the buffer, such that glucose homeostasis is maintained.


2021 ◽  
Vol 19 (1) ◽  
pp. 85-90
Author(s):  
L. I. Tsidik ◽  

The neurotic disorders questionnaire was originally created on the basis of the classical test theory and does not meet the requirements of modern psychometrics. Within the framework of our research, this technique has been modified and consists of 13 scales, the psychometric analysis of which included all the technical stages of iterative analysis and scale modeling based on the Rush metric system. This article presents the results of clinical validation of four of them. Purpose of the study. To assess the clinical effectiveness of the scales of coping deficit, anankasticity, the scale of impulsivity and addictive reactions, as well as the scale of general personal disorganization of the modified version of the questionnaire of neurotic disorders. Material and methods. 296 people were examined. Among them, 167 are women and 129 are men. Statistical methods of the study are factor analysis of standardized residuals, ROC analysis, correlation analysis. Results: The studied scales are homogeneous in their structure. Using the ROC-analysis, high and moderate differentiating properties of the scales were revealed, cutoff values were calculated, which were the criteria for interpretation. Correlation analysis of the total indicator revealed statistically significant correlations between the studied scales and the MMPI scores, the QIDS-SR16 questionnaire, and the Hamilton Anxiety Rating Scale (HADS). Conclusions: The scales of coping deficit, anankasticity, the scale of impulsivity and addictive reactions, as well as the scale of general personal disorganization of the modified version of the neurotic disorders questionnaire are clinically valid and can be used to solve various practical problems.


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