Jabarali A - Profile on Academia.edu (original) (raw)

Papers by Jabarali A

Neutrosophic Sets and Systems, 2025

The Quadratic Transmuted Generalized Exponential Distribution (QTGED) enhances the generalized ex... more The Quadratic Transmuted Generalized Exponential Distribution (QTGED) enhances the generalized exponential distribution, making it a significant development for handling complex decision-making contexts. Traditional statistical distributions often focus on representing degrees of truth or membership in fuzzy sets, yet they struggle to capture situations involving incomplete, vague, or contradictory data accurately. This study introduces the Neutrosophic Quadratic Transmuted Generalized Exponential Distribution (NQTGED), specifically designed to address indeterminacy and transmuted data. Neutrosophic theory is essential here, as it overcomes the limitations of classical and fuzzy set theories by effectively managing uncertainty, indeterminacy, and inconsistency in data. By simultaneously representing truth, indeterminacy, and falsity, neutrosophic sets offer a comprehensive framework for modeling uncertainty. Traditional distributions lack the adaptability needed for evolving data complexities, often falling short when faced with non-standard data distributions or outliers. Addressing these challenges requires innovative approaches that incorporate advanced mathematical models for uncertainty. This is especially valuable in real-world situations, where data is frequently incomplete, imprecise, or contradictory, and sometimes transmuted. The study derives various mathematical properties of the model, assesses parameter estimation using maximum likelihood and simulation, and demonstrates practical applications with cancer remission data. Simulation results reveal that Neutrosophic Average Biases (NABs) and Neutrosophic Mean Square Errors (NMSEs) decrease as sample sizes increase, indicating strong and accurate parameter estimation. NQTGED provides superior fit and performance, offering significant insights for applications in reliability engineering and biomedical sciences.

Advances in Data Science and Adaptive Analysis, 2024

a predictive dashboard has been created to estimate the severity of depression, anxiety, and stre... more a predictive dashboard has been created to estimate the severity of depression, anxiety, and stress experienced by college students based on significant factors associated with their symptoms.

This research explores the link between adverse childhood experiences (ACEs) and cognitive emotio... more This research explores the link between adverse childhood experiences (ACEs) and cognitive emotional regulation (CER) in college students. ACEs are traumatic events during childhood, like abuse or neglect, that can affect mental health. CER is the ability to manage emotions through cognitive processes. This study is important for college students, who face academic and social pressures. Many students reflect on their childhood experiences and how they affect their current mental health. The study aims to understand how ACEs affect CER and mental health in college students, to improve mental health interventions. It highlights the need to address ACEs and promote effective CER strategies for better mental health in college students.

The long-term consequences of climate change have given a significant role in the economic develo... more The long-term consequences of climate change have given a significant role in the economic development of India. The purpose of this paper is to establish a time series vector error correction model for predicting the carbon dioxide emissions(CDE) based on a group of associated economic indicators (i.e. Gross Domestic Product(GDP), Energy Consumption(EC) and Trade(TR)). The CDEs are found to be cointegrated with GDP, EC and TR by employing Johansen's cointegration analysis. This paper addresses to the climate change studies by exploring the dynamic relationships between carbon dioxide emissions and the economic indicators using VEC model imposing cointegration restriction for India over the period 1971-2016. The developed Vector error correction(VEC) model is compared with auto-regressive integrated moving average(ARIMA) and vector auto-regressive(VAR) models for forecasting the long-term carbon dioxide emissions with forecast accuracy measure.

Obesity has been steadily growing from three decades and strongly associated with several disease... more Obesity has been steadily growing from three decades and strongly associated with several disease. There are several factors has been used for diagnose the obesity and over-weights. In this study, to select, explore and model the data-set of obesity level with food habits and physical activities using classification algorithms. The high accuracy and low error measures of classification algorithm is identified to predict the obesity level based on performance and error measures using WEKA.

Journal of Statistics and Management Systems, 2018

Tele-traffic is related to internet and other complex telecommunications systems. They include pa... more Tele-traffic is related to internet and other complex telecommunications systems. They include packet sizes, inter-arrival times, download times and transmission times, among others. Such times are followed by heavy tailed distribution. In this concern, the study of special type of M/G/1 queueing model with Burr type XII distribution is proposed for applications in tele-traffic. The limiting distribution, expected waiting time and expected busy period time are derived by using conventional technique. Finally the computational performances are carried out for evaluating this model.

International Journal of Pure and Applied Mathematics, 2016

This article deals the inter-arrival time of the customers of queueing model which follows Burr t... more This article deals the inter-arrival time of the customers of queueing model which follows Burr type XII distribution. The objective of this paper is, to examine the traffic congestion of Burr XII/M/1 queueing model with non-working and working vacation periods under the stability condition. The estimates of model parameters are done for these models through Bayesian approches based on different arbitrary values and samples under Gibbs sampler algorithm.

Hacettepe Journal of Mathematics and Statistics, 2016

Bayesian methodology is an important technique in statistics, and especially in mathematical stat... more Bayesian methodology is an important technique in statistics, and especially in mathematical statistics. It consists of the sample information along with the prior information available about the parameter before the sample has been observed. This paper exhibits the estimation of the parameters of queueing model with inter-arrival time and service time which follows Gumbel distribution. Bayesian procedure is applied to obtain the estimation of the model parameters and the trac intensity of queueing model based on the informative and the non-informative prior knowledges. In this paper, the Bayesian estimates are carried out by numerically and graphically with the help of Markov Chain Monte Carlo (MCMC) simulation technique, particularly in Gibbs sampling algorithm.

Journal of Library & Information Services in Distance Learning , 2024

The library and information services of the twenty first century are rapidly changing education l... more The library and information services of the twenty first century are rapidly changing education learning patterns because of the rapid development of electronic publishing libraries. However, the literature reveals the considerable unpredictability in experience, challenges, and awareness about E-resources among college students during and after the COVID-19 Pandemic scenario. In the aftermath of the pandemic, everyone has been forced to learn and teach E-resources in educational institutions worldwide. Along with their academic demands, college students are confronted by a lack of knowledge of handling e-learning resources and low network connectivity in remote regions. In this aspect, this study commenced to describe the experience, challenges, and awareness about e-learning resources. A descriptive and diagnostic research design was adopted and primary data was collected from college students through Google Forms with participant consent. The basic information about respondents, experience, challenges, and awareness of E-resources are tools of the study. The statistical analysis is to be carried out based on the study's objective. This analysis was used to identify influential factors and to explore the relationships between e-learning experience, and resource awareness. Subsequently, the analysis is used to discuss recommendations for enhancing the utilization of e-learning resources based on the study's findings.

International Journal of Neutrosophic Science, 2024

The study of neutrosophy offers a fresh approach for handling uncertain data with adaptability. T... more The study of neutrosophy offers a fresh approach for handling uncertain data with adaptability. This article explores the application of neutrosophic probability distribution in constructing a transmuted neutrosophic framework. Specifically, it introduces a generalized transmuted neutrosophic distribution. Building upon this generalization, quadratic and cubic transmuted distributions are developed and examined alongside certain lifetime distributions serving as foundational neutrosophic models. Additionally, an empirical investigation is conducted to assess the practicality and versatility of these distributions in real-world contexts.

Applied Mathematical Sciences, 2015

According to Paxson & Floyd[8], the regular assumption of the exponential times of the inter-arri... more According to Paxson & Floyd[8], the regular assumption of the exponential times of the inter-arrival time and service time are vanished when heavy tailed scenaro. Consider the single server queue with multiple working vacation and the regular service time which follows Gumbel distribution. This paper exhibits the estimation of the parameters of queueing model under Bayesian procedure based on gibbs sampling algorithm through Markov Chain Monte Carlo(MCMC) technique. The performances of the empirical estimates of the model parameters and traffic intensity are discussed.

In this paper concerned with the study of queueing model for teletraffic. In teletraffic data are... more In this paper concerned with the study of queueing model for teletraffic. In teletraffic data are related to internet and other complex
telecommunications systems. They include packet sizes, inter-arrival times, download times and transmission times, among others. Such
times are follows to Gumbel distribution. The limiting distribution, expected waiting time and expected busy period time are derived by
using embedded Markov chain technique. Finally the computational performances are carried out for this model.

Keywords: M/G/1 queue, Gumbel distribution, embedded Markov chain, teletraffic data.

This paper exhibits the estimation of the parameters of queueing model with multiple working vaca... more This paper exhibits the estimation of the parameters of queueing model with multiple working vacation period under regular service time which follows Gumbel distribution. Bayesian procedure is applied to obtain the estimation of the model parameters with the use of informative and non-informative prior knowledges and the traffic intensity of queueing model is also obtained. Here, the Bayesian estimation is carried out numerically and graphically with the help of simulation technique based on Markov Chain Monte Carlo(MCMC).

Queue is a waiting line phenomenon. The server may take the vacation due to breakdown or other re... more Queue is a waiting line phenomenon. The server may take the vacation due to breakdown or other reasons. If the server is on vacation, there is a situation the customers have to wait for service during that period. The generalization of the classical vacation model is considered as the server which gives the service at different rate rather than completely stopping the service during the vacation period. This paper deals with the estimation of the parameters in M/M/1 queue during working vacations period. The maximum likelihood estimation procedure is applied to obtain the estimation of the model parameters and also the performance measure of queueing system had been discussed. Finally computational results are presented for the queueing model.
Keywords: M/M/1 queue, vacation model, working vacations, maximum likelihood estimation, performance measures.