Journal of Reliability and Statistical Studies

A Study on One-Parameter Entropy-Transformed Exponential Distribution and Its Application

Mathew Stephen — 2024-06-05

This study presents the Entropy-Transformed Exponential Distribution (EnTrED), in an attempt to enhancing the flexibility and applicability of the traditional exponential distribution. The study explores the statistical properties of the EnTrED, including mode, quantile function, reliability, moments, and hazard function. The parameters of the distribution were estimated using maximum likelihood estimation, and the stability of these estimates was thoroughly evaluated through extensive Monte Carlo simulation. The simulation results demonstrated that the maximum likelihood estimates of the model parameters were well-behaved. Additionally, Empirical assessments against alternative distributions underscores the robustness of the EnTrED as a superior model for analyzing life data.

Analysis of EAC Using Multiple Regression and Conditional Process: A Statistical Approach

Muskan Singh — 2024-07-03

In the modern world of increased competition, evolving technologies and volatile environment every institution must poise themselves to innovate and change, not only to prosper but merely to survive. The situation is more acute in institutions of higher education in India where things are changing with unprecedented speed. The survival of the institutions will depend upon the adaptability of their employees to embrace the change. However, employees’ acceptance to change cannot be developed overnight and also in isolation. It requires intensity and persistency of efforts in the right direction from the management. In the present paper, the researchers have identified the role of emotional intelligence and locus of control in enhancing employees’ acceptance to change in HEIs, Uttarakhand using multiple regression and conditional process analysis. The data for the present study were collected using stratified sampling and structured questionnaires from 432 employees from various HEIs in Uttarakhand. The finding revealed that EI enhances the EAC in HEI. Further, it also revealed that Job Satisfaction acts as a partial mediator in the relation between EI and EAC.

Optimizing Resource Allocation in M/M/1/N Queues with Feedback, Discouraged Arrivals, and Reneging for Enhanced Service Delivery

Savita — 2024-06-05

This article presents a novel computational approach for analyzing M/M/1/N queues with feedback, discouraged arrivals, and reneging, under the first-come, first-served (FCFS) discipline. We calculate explicit transient state probabilities and represent results using symmetric tridiagonal matrix eigenvalues. Through numerical simulations, we validate our method, providing practical insights for optimizing resource allocation. Our study contributes to both theory and application, advancing queueing theory and aiding decision-makers in improving service quality and resource management.

A Review Based on Various Applications to Find a Consistent Pairwise Comparison Matrix

Shalu Kaushik — 2024-06-05

Multi-criteria decision-making (MCDM) is a crucial process that provides a systematic approach to resolving numerous challenging problems encountered in everyday life. An effective method for addressing such MCDM challenges is the Analytic Hierarchy Process (AHP). Within AHP, the resolution of these problems relies on the Pairwise Comparison Matrix (PCM), a pivotal component of the decision-making framework. A fundamental aspect of AHP lies in ensuring the consistency of the comparison matrix to validate the logical perspective of the respondents. An inconsistent matrix undermines its utility as a reference for decision-making, underscoring the significance of achieving consistency in the PCM as a pivotal stage in the decision-making process. In this discourse, we delve into various methodologies aimed at deriving a refined and consistent PCM capable of replacing the original inconsistent version. To facilitate comprehension, we categorize the references based on proposed approaches and specific focal points.

Modeling Software Release Time and Software Patch Release Time Based on Testing Effort and Warranty

Palak Saxena — 2024-06-05

In this world of software technology, our dependency on software’s is increasing continuously. As a result, software industries are working hard to develop highly reliable software and to meet the expectation of customers. Generally, software companies release software early in market to take gain market share, but rigorous software testing is required for early release software to ensure reliability of software and meet the customer’s expectations. This requires a huge amount of resources, and it increases financial burden on the company, consequently, decreases the overall profit of company. Further, late release due to prolong testing of a software may improves reliability but results into a loss of market opportunity cost or may not be fulfil the customer’s aspirations. As a result, to stay competitive, companies release software early and release patches later to fix the bugs, improve the functionality of software, and to update the software. Software industries are improving the performance or usability of software by releasing patches which may increase the consumption of testing effort and consequently increase in cost. On the other hand, software firms also provide warranty on their products. To address the above said issues, we have developed a testing effort-based software reliability growth model, which incorporates warranty policy and estimates the optimal software release and patch time with the objective to minimise the total testing cost. Further, we have used Genetic Algorithm (GA) to estimate optimum software release and patch time. A numerical illustration has been presented on a real time data set to validate the proposed model.