Application of the logistic regression for determining transition probability matrix of operating states in the transport systems

Kozłowski, Edward; Borucka, Anna; Świderski, Andrzej

doi:10.17531/ein.2020.2.2

Cited by 26 publications

(28 citation statements)

References 43 publications

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“…Then the authors calculated average scores of individual IT tools (Table 1) and checked whether the differences between them are statistically significant. To do that, the authors used the non-parametric Kruskal-Wallis test with the null hypothesis that all observations come from one population (Kozłowski, Borucka and Świderski, 2020). The calculated p-value is 0.034, which means that for the adopted confidence level =0.05, the null hypothesis should be rejected in favour of the alternative hypothesis, stating that there are significant differences between average scores of individual IT tools assessed by lecturers and that the choice of a specific application has an impact on the quality of teaching.…”

Section: Results Of the Questionnaire Survey For Employeesmentioning

confidence: 99%

Higher Education – Related Problems During Covid-19 Pandemic

Slaski¹,

Grzelak²,

Rykala³

2020

ERSJ

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Purpose: The article aims to analyze the opportunities and threats stemming from remote learning, to assess the impact of the use of modern technologies on the quality of the education process, as well as to study the level of students' satisfaction with distance learning. Design/Methodology/Approach: The deduction method was used to assess the observations made in connection with the introduction of restrictions related to higher education in individual countries worldwide, while the induction method was used to formulate conclusions based on the relevant information collected. The empirical observation method was used to diagnose the main problems resulting from remote education and was also relied upon to examine the potential use of modern technologies to improve the quality of the process. Data was collected based on a survey concerned with the participation of logistics students in classes conducted remotely. Findings: The surveys conducted aimed at assessing the organization and conducting classes in the remote mode, based on modern educational methods. The research conducted allows us to perform a comprehensive evaluation of the quality of remote education of logistics students and determine its impact on acquiring knowledge and practical skills. The research provides information concerning the impact that modern training technologies have on the level of students' training and the expansion of their professional competence and experience. Practical Implications: The present article will make it possible to assess the functioning of higher education institutions in the pandemic and show opportunities and threats for distance education and perspectives for the future functioning of higher education. Originality/Value: The article presents an analysis of opportunities and threats and examples of good practices and recommendations, which can be followed if classroom learning continues to be suspended.

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Section: Results Of the Questionnaire Survey For Employeesmentioning

confidence: 99%

Higher Education – Related Problems During Covid-19 Pandemic

Slaski¹,

Grzelak²,

Rykala³

2020

ERSJ

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“…The need to check Markov's property is discussed in more detail in the literature [10,11], while less attention is paid to the distribution of variables studied. Therefore, this publication compares the results of process examination according to the semi-Markov model for variables of non-parametric distribution with the analysis according to the Markov model, in which their exponential form was (falsely) assumed.…”

Section: The Aim Of the Studymentioning

confidence: 99%

“…In the first stage, the lack of memory characteristic of the process was assessed. The goodness of fit test χ 2 was used for the study, defining at the level of significance α = 0.05 the zero hypothesis assuming that the chain studied meets the Markov property, and the alternative hypothesis that the Markov property is not met [11]. The test statistic χ 2 = 228.7, while related to it p-value = 0.264, which means that there are no grounds to reject the zero hypothesis on the chain meeting the Markov property.…”

Section: Studying Markov's Propertymentioning

confidence: 99%

“…Markov processes concern exponential distributions, the most popular ones in reliability theory [11,35]. They are described by two parameters, which fully define them.…”

Section: Calculations According To the Markov Modelmentioning

confidence: 99%

“…Identifying a model without meeting this assumption may lead to false conclusions, which is suggested by many authors [8,9]. They point out that ignoring the Markov property examination will results in incorrect analysis results, e.g., Shi et al [10], Zhang et al [8], or Kozłowski et al [11]. Therefore, it is necessary to examine the randomness of sequences of subsequent operational states, as it is done by Yang et al [12] or Komorowski and Raffa [13].…”

Section: Background Introduction To the Studymentioning

confidence: 99%

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Evaluation of Machinery Readiness Using Semi-Markov Processes

et al. 2020

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This article uses Markov and semi-Markov models as some of the most popular tools to estimate readiness and reliability. They allow to evaluate of both individual elements as well as entire systems—including production systems—as multi-state structures. To be able to distinguish states with varying degrees of technical readiness in complicated and complex objects (systems) allows to determine their individual impact on the tasks performed, as well as on the total reliability. The application of the Markov process requires, for the process dwell times in the individual states, to be random variables of exponential distribution and the fulfilling Markov’s property of the independence of these states. Omitting these assumptions may lead to erroneous results, which was the authors’ intention to show. The article presents a comparison of the results of the examination of the process of non-parametric distribution with an analysis in which its exponential form was (groundlessly) assumed. Significantly different results were obtained. The aim was to draw attention to the inconsistencies obtained and to the importance of a preliminary assessment of the data collected for examination. The diagnostics of the machine readiness operating in the studied production company was additionally performed. This allowed to evaluate its operational potential, especially in the context of solving process optimization problems.

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