scholarly journals Mapping Computations in Heterogeneous Multicore Systems with Statistical Regression on Program Inputs

2021 ◽  
Vol 20 (6) ◽  
pp. 1-35
Author(s):  
Junio Cezar Ribeiro Da Silva ◽  
Lorena Leão ◽  
Vinicius Petrucci ◽  
Abdoulaye Gamatié ◽  
Fernando Magno Quintão Pereira
Keyword(s):  
Linear Regression ◽  
Heterogeneous System ◽  
Multivariate Linear Regression ◽  
Statistical Regression ◽  
Efficient Tool ◽  
Heterogeneous Multicore ◽  
Heterogeneous Architectures ◽  
Java Bytecode ◽  
Hardware Configuration ◽  
Adaptive Compilation

A hardware configuration is a set of processors and their frequency levels in a multicore heterogeneous system. This article presents a compiler-based technique to match functions with hardware configurations. Such a technique consists of using multivariate linear regression to associate function arguments with particular hardware configurations. By showing that this classification space tends to be convex in practice, this article demonstrates that linear regression is not only an efficient tool to map computations to heterogeneous hardware, but also an effective one. To demonstrate the viability of multivariate linear regression as a way to perform adaptive compilation for heterogeneous architectures, we have implemented our ideas onto the Soot Java bytecode analyzer. Code that we produce can predict the best configuration for a large class of Java and Scala benchmarks running on an Odroid XU4 big.LITTLE board; hence, outperforming prior techniques such as ARM’s GTS and CHOAMP, a recently released static program scheduler.

scholarly journals Association between triglyceride-glucose index and risk of arterial stiffness: a cohort study

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Shouling Wu ◽  
Luli Xu ◽  
Mingyang Wu ◽  
Shuohua Chen ◽  
Youjie Wang ◽  
...  
Keyword(s):  
Growth Rate ◽  
Linear Regression ◽  
Arterial Stiffness ◽  
Multivariate Linear Regression ◽  
Annual Growth ◽  
Annual Growth Rate ◽  
Cross Sectional ◽  
Tyg Index ◽  
Longitudinal Association ◽  
The Cross

Abstract Background Triglyceride–glucose (TyG) index, a simple surrogate marker of insulin resistance, has been reported to be associated with arterial stiffness. However, previous studies were limited by the cross-sectional design. The purpose of this study was to explore the longitudinal association between TyG index and progression of arterial stiffness. Methods A total of 6028 participants were derived from the Kailuan study. TyG index was calculated as ln [fasting triglyceride (mg/dL) × fasting glucose (mg/dL)/2]. Arterial stiffness was measured using brachial-ankle pulse wave velocity (baPWV). Arterial stiffness progression was assessed by the annual growth rate of repeatedly measured baPWV. Multivariate linear regression models were used to estimate the cross-sectional association of TyG index with baPWV, and Cox proportional hazard models were used to investigate the longitudinal association between TyG index and the risk of arterial stiffness. Results Multivariate linear regression analyses showed that each one unit increase in the TyG index was associated with a 39 cm/s increment (95%CI, 29–48 cm/s, P < 0.001) in baseline baPWV and a 0.29 percent/year increment (95%CI, 0.17–0.42 percent/year, P < 0.001) in the annual growth rate of baPWV. During 26,839 person-years of follow-up, there were 883 incident cases with arterial stiffness. Participants in the highest quartile of TyG index had a 58% higher risk of arterial stiffness (HR, 1.58; 95%CI, 1.25–2.01, P < 0.001), as compared with those in the lowest quartile of TyG index. Additionally, restricted cubic spline analysis showed a significant dose–response relationship between TyG index and the risk of arterial stiffness (P non-linearity = 0.005). Conclusion Participants with a higher TyG index were more likely to have a higher risk of arterial stiffness. Subjects with a higher TyG index should be aware of the following risk of arterial stiffness progression, so as to establish lifestyle changes at an early stage.

scholarly journals 2011. Reaction of Clinicians to Positive Respiratory Viral Panels in Non-critically Ill Patients Without Bacterial Infection

2019 ◽  
Vol 6 (Supplement_2) ◽  
pp. S675-S675
Author(s):  
Jason C Gallagher ◽  
Sara Lee ◽  
Leah Rodriguez ◽  
Jacqueline Emily Von Bulow ◽  
Kaede Ota Sullivan
Keyword(s):  
Linear Regression ◽  
Bacterial Infection ◽  
Linear Regression Analysis ◽  
Solid Organ Transplantation ◽  
Retrospective Chart Review ◽  
Multivariate Linear Regression ◽  
Antibiotic Prescribing ◽  
Antibiotic Administration ◽  
Multivariate Linear Regression Analysis ◽  
Solid Organ

Abstract Background Respiratory viral panels (RVPs) can detect multiple viral pathogens and give clinicians diagnostic confidence to discontinue antibiotics. However, relatively little is known about how these tests influence antibiotic prescribing in hospital settings. Methods This was a 26-month retrospective chart review of patients with positive RVPs. Hospitalized adults receiving antibiotics at the time of the RVP were included. Exclusion criteria were: ICU care, solid-organ transplantation (SOT), positive RVP for influenza, positive bacterial cultures, and antibiotic administration for bacterial infection (e.g., cellulitis). A multivariate linear regression model was created to investigate associations with longer antibiotic use after a positive RVP. Results 1,346 patients were screened and 242 met inclusion criteria. Primary reasons for exclusion were SOT, ICU, and influenza diagnosis. Patients were a median age of 60.5 years [IQR 51,70] and 35.5% were men. The median length of stay (LOS) was 4 days [IQR 3.6]. 233 patients (6.3%) had chest radiology performed, of which 71 (30.4%) had possible pneumonia noted. 50 (20.7%) were immunocompromised (IC). 199 (82.2%) had a history of pulmonary disease, most commonly COPD. Rhinovirus was isolated in 156 patients (64.5%), followed by metapneumovirus (35, 14.9%) and RSV (32, 13.3%). Antibiotics were given for a median total of 3 days [IQR 3.6]; they were discontinued within 24 hours of the RVP result in 107 patients (44.2%). Conclusion In this population of patients with viral infection and no discernable bacterial infection, 44.2% of patients had antibiotics discontinued within 24 hours of RVP results. On multivariate linear regression analysis, younger age, longer LOS, and IC status were associated with longer antibiotic duration after a positive RVP. A comparison with patients with negative RVP results could reveal if the test prompted discontinuation. Disclosures All authors: No reported disclosures.

Fuzzy C-Regression Models

2013 ◽  
Vol 278-280 ◽  
pp. 1323-1326
Author(s):  
Yan Hua Yu ◽  
Li Xia Song ◽  
Kun Lun Zhang
Keyword(s):  
Linear Regression ◽  
Least Squares ◽  
Linear Models ◽  
Least Squares Method ◽  
Least Square Method ◽  
Least Square ◽  
Estimation Methods ◽  
Statistical Regression ◽  
Fuzzy Linear Regression ◽  
Fuzzy Degree

Fuzzy linear regression has been extensively studied since its inception symbolized by the work of Tanaka et al. in 1982. As one of the main estimation methods, fuzzy least squares approach is appealing because it corresponds, to some extent, to the well known statistical regression analysis. In this article, a restricted least squares method is proposed to fit fuzzy linear models with crisp inputs and symmetric fuzzy output. The paper puts forward a kind of fuzzy linear regression model based on structured element, This model has precise input data and fuzzy output data, Gives the regression coefficient and the fuzzy degree function determination method by using the least square method, studies the imitation degree question between the observed value and the forecast value.

Correlation between FA and ADC, number and length of the periprostatic neurovascular fibers

2021 ◽  
pp. 039156032110637
Author(s):  
Valerio Di Paola ◽  
Angelo Totaro ◽  
Giacomo Avesani ◽  
Benedetta Gui ◽  
Andrea Boni ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
Negative Correlation ◽  
Multivariate Regression ◽  
Linear Regression Analysis ◽  
Multivariate Linear Regression ◽  
Multivariate Linear Regression Analysis ◽  
Independent Variables ◽  
Fiber Tracts ◽  
Good Agreement

Purpose: Our aim was to explore the relation between FA and ADC, number and length of the periprostatic neurovascular fibers (PNF) by means of 1.5 T Diffusion Tensor Imaging (DTI) imaging through a multivariate linear regression analysis model. Methods: For this retrospective study, 56 patients (mean age 63.5 years), who underwent 1.5-T prostate MRI, including DTI, were enrolled between October 2014 and December 2018. Multivariate regression analysis was performed to evaluate the statistically significant correlation between FA values (dependent variable) and ADC, the number and the length of PNF (independent variables), if p-value <0.05. A value of 0.5 indicated poor agreement; 0.5–0.75, moderate agreement; 0.75–0.9, good agreement; 0.61–0.80, good agreement; and 0.9–1.00, excellent agreement. Results: The overall fit of the multivariate regression model was excellent, with R2 value of 0.9445 ( R2 adjusted 0.9412; p < 0.0001). Multivariate linear regression analysis showed a statistically significant correlation ( p < 0.05) for all the three independent variables. The r partial value was −0.9612 for ADC values ( p < 0.0001), suggesting a strong negative correlation, 0.4317 for the number of fiber tracts ( p < 0.001), suggesting a moderate positive correlation, and −0.306 for the length of the fiber tracts ( p < 0.05), suggesting a weak negative correlation. Conclusions: Our multivariate linear regression model has demonstrated a statistically significant correlation between FA values of PNF with other DTI parameters, in particular with ADC.

scholarly journals Short period PM2.5 prediction based on multivariate linear regression model

PLoS ONE ◽  
2018 ◽  
Vol 13 (7) ◽  
pp. e0201011 ◽  
Author(s):  
Rui Zhao ◽  
Xinxin Gu ◽  
Bing Xue ◽  
Jianqiang Zhang ◽  
Wanxia Ren
Keyword(s):  
Linear Regression ◽  
Regression Model ◽  
Linear Regression Model ◽  
Multivariate Linear Regression ◽  
Multivariate Linear Regression Model ◽  
Short Period

Life satisfaction and its relationship with spiritual well-being and religious practice in Iranian adolescent girls

2017 ◽  
Vol 31 (6) ◽  
Author(s):  
Fariba Alizadeh Sharajabad ◽  
Sakineh Mohammad-Alizadeh Charandabi ◽  
Mojgan Mirghafourvand
Keyword(s):  
Life Satisfaction ◽  
Linear Regression ◽  
Adolescent Girls ◽  
Well Being ◽  
Religious Practice ◽  
Multivariate Linear Regression ◽  
Multivariate Linear Regression Analysis ◽  
Income Status ◽  
Spiritual Well Being ◽  
The Mean

Abstract Introduction During recent years, special attention has been given to spiritual well-being and religious practice in the field of health. This study aimed to determine the predictors of life satisfaction among adolescent girls in Tabriz, Iran, 2015. Materials and methods This cross-sectional study was conducted on 520 female students studying in high schools who were selected using the cluster sampling method. Data collection was carried out through the questionnaires of socio-demographic characteristics, spiritual well-being (SWBS), religious practice (Arcury and colleagues) and life satisfaction (SWLS). Multivariate linear regression model was used for data analysis. Results The mean score of life satisfaction was 22.0 (SD: 6.0) from the attainable score of 5–35. The mean score (SD) of spiritual well-being was 90.2 (16.2), ranging from 20 to 120. The mean score of the religious practice was 32.1 (10.5) out of the achievable score range of 0–60. Multivariate linear regression analysis showed that existential well-being and sufficiency of income for expenses were predictors of life satisfaction and they explained 41.8% of the variance in the life satisfaction score. Conclusion The findings of the present study confirm the importance of existential well-being and a modifiable variable (sufficiency of income) in the life satisfaction. Thus, it is necessary to provide strategies to promote spirituality and improve the income status for improving adolescents’ life satisfaction.

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