Applicability of correlational data-mining to small-scale turbojet performance map generation

Turbojet applications benefit from accurate performance models. The aim of this study is to explore the applicability of data-mining algorithms to determine relationships between the generated thrust, the environmental conditions (free stream air-speed, inlet temperature and pressure) and the operating conditions (input fuel flow and shaft angular speed). For this purpose, experimental tests were carried out within wind-tunnel facilities using an experimental single-spool turbojet test bench. It is well-known that a large set of data-mining approaches relies on establishing linear correlations among input and output variables. The scope of this article is to assess the applicability of correlational data-mining approaches by i) an exploratory data analysis to find underlying data patterns and ii) principal component regressions to obtain a suitable predictive model for the generated thrust. Validation experiments demonstrated that the data-based model allows capturing the effects of the environmental and operating conditions with good accuracy (Root Mean Squared Error RMSE = 3.5100%), while maintaining a low complexity in the resulting structure. These results show that it is possible to generate turbojet experimental performance maps through data-mining algorithms with a correlational approach.

Causal Relationships in Longitudinal Observational Data: An Integrative Modelling Approach

Much research in psychology relies on data from observational studies that traditionally do not allow for causal interpretation. However, a range of approaches in statistics and computational sciences have been developed to infer causality from correlational data. Based on conceptual and theoretical considerations on the integration of interventional and time-restrainment notions of causality, we set out to design and empirically test a new approach in order to identify potential causal factors in longitudinal correlational data. A principled and representative set of simulations and an illustrative application to identify early-life determinants of cognitive development in a large cohort study are presented. The simulation results illustrate the potential but also the limitations for discovering causal factors from observational data. In the illustrative application, plausible and reasonably well-established early life determinants of cognitive abilities in 5-year-old children were identified. Based on these results, we discuss the possibilities of using exploratory causal discovery in psychological research but also highlight its limits and potential misuses and misinterpretations.

P017 Am I sleepy? – Subjective Sleepiness and Drowsy Driving: A systematic review and meta-analysis

Introduction Driving impairment due to sleep loss is a major contributor to motor vehicle crashes resulting in severe injury or fatalities. Ideally, drivers should be aware of their sleepiness and cease driving to reduce risk of a crash. However, there is little consensus on how accurately drivers can identify sleepiness, and how this relates to subsequent driving impairment. To examine whether drivers are aware of their sleepiness, we systematically reviewed the literature. Methods The research question for this review was “are drivers aware of sleepiness while driving, and to what extent does subjective sleepiness accurately reflect driving impairment?”. Our search strategy led to thirty-four simulated/naturalistic driving studies for review. We then extracted the relevant data. Correlational data were examined using meta-analysis, while predictive data were assessed via narrative review. Results Results showed that drivers were aware of sleepiness, and this was associated with both driving impairment and physiological drowsiness. Overall, subjective sleepiness was more strongly correlated (a) with ocular and EEG-based outcomes (rweighted = .70 and .73, respectively, p<.001), rather than lane position and speed outcomes (rweighted = .46 and .49, respectively, p<.001); (b) under simulated driving conditions compared to naturalistic drives; and (c) when the Karolinska Sleepiness Scale was used to measure subjective sleepiness. Lastly, high levels of sleepiness significantly predicted crash events and lane deviations. Discussion This review presents evidence that drivers are aware of sleepiness when driving, and suggests that interventions such as stopping driving when feeling ‘sleepy’ may significantly reduce crash risk.

Chain graph reduction into Power Chain Graphs

Reduction of graphs is a class of procedures used to decrease the dimensionality of a given graph in which the properties of the reduced graph are to be induced from the properties of the larger original graph. This paper introduces both a new method for reducing chain graphs to simpler directed acyclic graphs (DAGs), that we call power chain graphs (PCG), as well as a procedure for structure learning of this new type of graph from correlational data of a Gaussian Graphical model (GGM). A definition for PCGs is given, directly followed by the reduction method. The structure learning procedure is a two-step approach: first, the correlation matrix is used to cluster the variables; and then, the averaged correlation matrix is used to discover the DAGs using the PC-stable algorithm. The results of simulations are provided to illustrate the theoretical proposal, which demonstrate initial evidence for the validity of our procedure to recover the structure of power chain graphs. The paper ends with a discussion regarding suggestions for future studies as well as some practical implications.

The Underappreciated Effects of Unreliability on Multiple Regression and Mediation

There is an increasing trend for researchers in the social sciences to draw causal conclusions from correlational data. Even researchers who use relatively causally neutral language in describing their findings, imply causation by including diagrams with arrows. Moreover, they typically make recommendations for intervention or other applications in their discussion sections, that would make no sense without an implicit assumption that the findings really do indicate causal pathways. The present manuscript commences with the generous assumption that regression-based procedures extract causation out of correlational data, with an exploration of the surprising effects of unreliability on causal conclusions. After discussing the pros and cons of correcting for unreliability, the generous assumption is questioned too. The conclusion is that researchers should be more cautious in interpreting findings based on correlational research paradigms.

Correlation between the strength of muscle actions of the paretic lower-limb and gait speed after Stroke: Results of a meta-analysis of six studies

BACKROUND AND OBJECTIVE: Lower limb strength, particularly of the more paretic side, is known to correlate with comfortable gait speed. This meta-analysis sought to determine the relative value of 6 muscle group strengths as explanators of comfortable gait speed. METHODS: Relevant literature was sought using PubMed, CINAHL Scopus, and a hand search. Information on samples, measurements, and correlations were extracted. Correlational data were subjected to meta-analysis. RESULTS: Results from 6 studies were consolidated. The summary correlations between paretic lower limb strength and comfortable gait speed ranged from 0.45 to 0.61. Data were highly heterogeneous but did not show publication bias. CONCLUSIONS: The correlation between the lower limb strength and comfortable gait speed strength is moderate. However, it does not provide an adequate explanation to guide clinical practice.

Correlation of grip and knee extension strength in mature adults

BACKROUND AND OBJECTIVE: Grip and knee strength are commonly measured but controversy exists as to whether either is a proxy for the other. The purpose of this meta-analysis was to summarize the correlation between the 2 variables. METHODS: Relevant literature was sought using PubMed, Google, and a hand search. Information on populations, measurements, and correlations were extracted. Correlational data were subjected to meta-analysis. RESULTS: Results from 17 studies were consolidated. The summary correlation between grip and knee extension strength was 0.64 with 95% CI of 0.57 to 0.71. Data were highly heterogeneous but did not show publication bias. CONCLUSION: The correlation between the grip and knee extension strength is good. However, it is not good enough to justify using either as a proxy for the other.

Regulatory compliance and environmental sustainability practices of manufacturing entrepreneurial ventures in Uganda

Purpose The purpose of this paper is to establish whether all the dimensions of regulatory compliance matter for environmental sustainability practices of manufacturing small and medium entrepreneurial ventures (SMEVs) using evidence from Uganda. Design/methodology/approach This study is cross-sectional and correlational. Data was collected through a questionnaire survey of 106 manufacturing SMEVs. Data was analyzed using Statistical Package for Social Sciences (SPSS) version 23. Findings The results indicate that controls, legitimacy and deterrence do matter for environmental sustainability practices of the manufacturing SMEVs in Uganda, unlike social norms and values. Originality/value This study fosters the understanding of environmental sustainability practices, as it provides insights on whether all the dimensions of regulatory compliance do matter for environmental sustainability practices of manufacturing SMEVs in Uganda.

Correlation analysis to investigate unconscious mental processes: A critical appraisal and mini-tutorial

As a method to investigate the scope of unconscious mental processes, researchers frequently obtain concurrent measures of task performance and stimulus awareness across participants. Even though both measures might be significantly greater than zero, the correlation between them might not, encouraging the inference that an unconscious process drives task performance. We highlight the pitfalls of this null-correlation approach and provide a mini-tutorial on ways to avoid them. As reference, we use a recent study by Salvador, Berkovitch, Vinckier, Cohen, Naccache, Dehaene, and Gaillard (2018) reporting a non-significant correlation between the extent to which memory was suppressed by a Think/No-Think cue and an index of cue awareness. In the Null Hypothesis Significance Testing (NHST) framework, it is inappropriate to interpret failure to reject the null hypothesis (i.e., correlation = 0) as evidence for the null. Furthermore, psychological measures are often unreliable, which can dramatically attenuate the size of observed correlations. A Bayesian approach can circumvent both problems and compare the extent to which the data provide evidence for the null versus the alternative hypothesis (i.e., correlation > 0), while considering the usually low reliabilities of the variables. Applied to Salvador et al.’s data, this approach indicates no to moderate support for the claimed unconscious nature of participants’ memory-suppression performance—depending on the model of the alternative hypothesis. Hence, more reliable data are needed. When analyzing correlational data, we recommend researchers to employ the Bayesian methods developed here (and made freely available as R scripts), rather than standard NHST methods, to take account of unreliability.

Correlation of paretic knee extension strength with gait speed after stroke: A meta-analysis

BACKGROUND AND OBJECTIVE: Numerous studies have addressed the relationship between paretic knee extension strength and comfortable walking speed after stroke. However, the correlations reported are highly variable. This review sought to summarize the correlational data using meta-analysis. METHODS: Relevant literature was identified via a search of 3 bibliographic databases. Articles were screened and perused for inclusion. Included articles were examined for information on the sample studied, procedures for measuring strength and gait speed, and correlations reported between the 2 variables. Meta-analysis was used to calculate a summary correlation. RESULTS: Of 299 unique articles, 18 met inclusion criteria. Articles were diverse in regard to samples studied, procedures described, and correlations reported. Meta-analysis using data from all included studies revealed a summary correlation of 0.51. For studies using hand-held or isokinetic dynamometry, the summary correlation was 0.46 and 0.59 respectively. CONCLUSIONS: This study provides a better indication of the correlation between paretic knee extension strength and comfortable gait speed than individual studies. The correlation is high enough to provide support for the routine measurement of paretic knee extension force for individuals who have experienced a stroke.