Application Of Statistics In Engineering Technology Programs

Zhan, Wei; Fink, Rainer; Fang, Alexander W.

doi:10.19030/ajee.v1i1.793

Cited by 7 publications

(5 citation statements)

References 28 publications

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“…The Pearson correlation coefficient was used to determine the correlations between the COF and AE amplitudes, as well as the energies between them, whose values higher than 0.75 indicate a high correlation between these parameters. The results of the p test show the percentages of the confidence levels of the results obtained [43][44][45].…”

Section: Methodsmentioning

confidence: 99%

Stick-Slip Phenomena and Acoustic Emission in the Hertzian Linear Contact

2022

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AE detection and analysis usually requires a specific, costly platform due to its particular burst nature and high-frequency content. This experimental study investigates the relationship between low-demand acoustic emission parameters (AE) and the occurrence of stick–slip (SS) at the Hertzian linear contact. Hence, the correlation of basic AE characteristics (amplitude, energy, and evolution in time) with stick–slip characteristics (static and kinetic friction coefficients, amplitude, energy, and evolution in time) is pursued. Tribological tests were conducted on cylinder–plane specimens under dry friction conditions with different loads at different low driving speeds and Hertzian contact pressures at a constant stiffness. The AE, normal, and friction forces were recorded simultaneously on the experimental stand. At the cylinder–plane interface, the jumps specific to the stick–slip phenomenon (friction coefficient—COF) were followed after a few milliseconds by AE jump peaks. The results of the experiments show that the amplitude and energy generated by AE were sensitive to the occurrence of the stick–slip phenomenon, while the AE and COF energies in the stick and slip phases had the same law of variation based on the driving velocities. The results show that the amplitude and energy of the sampled low-frequency AE signals were enough to detect the friction in SS and demonstrate the potential of AE as a tool for detecting and monitoring the tribological behaviour of SS at the linear Hertzian contact.

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Section: Methodsmentioning

confidence: 99%

Stick-Slip Phenomena and Acoustic Emission in the Hertzian Linear Contact

2022

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“…Statistics represent a multidisciplinary data exploration approach that has been effectively used in various fields such as engineering, physics, chemistry, economics, finance, commerce, computer science, and so on [35][36][37][38][39]. The effective use of different statistical techniques can help in examining the nature, distribution, and trends of data.…”

Section: Methodsmentioning

confidence: 99%

Performance Analysis of Statistical and Supervised Learning Techniques in Stock Data Mining

Sharma

Singh

2018

Data

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Nowadays, overwhelming stock data is available, which areonly of use if it is properly examined and mined. In this paper, the last twelve years of ICICI Bank’s stock data have been extensively examined using statistical and supervised learning techniques. This study may be of great interest for those who wish to mine or study the stock data of banks or any financial organization. Different statistical measures have been computed to explore the nature, range, distribution, and deviation of data. The different descriptive statistical measures assist in finding different valuable metrics such as mean, variance, skewness, kurtosis, p-value, a-squared, and 95% confidence mean interval level of ICICI Bank’s stock data. Moreover, daily percentage changes occurring over the last 12 years have also been recorded and examined. Additionally, the intraday stock status has been mined using ten different classifiers. The performance of different classifiers has been evaluated on the basis of various parameters such as accuracy, misclassification rate, precision, recall, specificity, and sensitivity. Based upon different parameters, the predictive results obtained using logistic regression are more acceptable than the outcomes of other classifiers, whereas naïve Bayes, C4.5, random forest, linear discriminant, and cubic support vector machine (SVM) merely act as a random guessing machine. The outstanding performance of logistic regression has been validated using TOPSIS (technique for order preference by similarity to ideal solution) and WSA (weighted sum approach).

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“…The problem-based approach is possible since many of the statistical approaches are needed in engineering (e.g. Six Sigma as in Zhan, Fink, and Fang 2010).…”

Section: Final Remarks and Future Workmentioning

confidence: 99%

Breaking the habit: engineering students’ understanding of mathematical creativity

Catarino

Nascimento

Morais

et al. 2017

European Journal of Engineering Education

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In higher education, engineering students have to be prepared for their future jobs, with knowledge but also with several soft skills, among them creativity. In this paper, we present a study carried on with 128 engineering undergraduate students on their understanding of mathematical creativity. The students were in the first year of different engineering first degrees in a north-eastern Portuguese university and we analysed the content of their texts for the question 'What do you understand by mathematical creativity?'. Data collection was done in the first semester of the academic years 2014/2015 and 2016/2017 in a Linear Algebra course. The results showed that 'problem solving' category had the majority of the references in 2014/2015, but not in the academic year 2016/2017 were 'involving mathematics' category had the majority. This exploratory study pointed out for 'problem solving' and 'involving mathematics' categories and gave us hints for teaching mathematics courses in engineering degrees. ARTICLE HISTORY

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Application Of Statistics In Engineering Technology Programs

Cited by 7 publications

References 28 publications

Stick-Slip Phenomena and Acoustic Emission in the Hertzian Linear Contact

Stick-Slip Phenomena and Acoustic Emission in the Hertzian Linear Contact

Performance Analysis of Statistical and Supervised Learning Techniques in Stock Data Mining

Breaking the habit: engineering students’ understanding of mathematical creativity

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