Modernization in the healthcare industry is happening with the support of artificial intelligence and blockchain technologies. Collecting healthcare data is done through any Google survey from different governing bodies and data available on the …

Early detection of dementia patients in advance is a great concern for the physicians. That is why physicians make use of multi modal data to accomplish this. The baseline visit data of the patients are mainly utilized for this task. Modern …

Real estate significantly contributes to the broader stock market and garners substantial attention from individual households to the overall country’s economy. Predicting real estate trends holds great importance for investors, policymakers, and …

Generalized linear mixed effect models (GLMEMs) are widely applied for the analysis of correlated non-Gaussian data such as those found in longitudinal studies. On the other hand, the Cox (proportional hazards, PHs) and the accelerated failure …

A mathematical approach to developing new distributions is reviewed. The method which composes of integration and the concept of a normalizing constant, allows for primitive interjection of new parameter(s) in an existing distribution to form new …

In the past decade, deep learning has greatly increased the complexity of industrial production intelligence by virtue of its powerful learning capability. At the same time, it has also brought security challenges to the field of industrial …

Search and recommendation are two essential features of any e-commerce website for finding and purchasing a specific product. Visual Search is a promising and quick method in comparison to a textual-based search method. Hence, the objective of …

This article, a new method for the diagnosis of Alzheimer’s disease in the mild stage is presented according to combining the characteristics of EEG signal and MRI images. The brain signal is recorded in four modes of closed-eyes, open eye …

Safer sexual practice is essential for improving women’s reproductive and sexual health outcomes. The goal of this study is to identify the contributing factors influencing safer sexual negotiations (SSN) through the application of machine …

This article introduced a three-parameter extension of the Generalized Rayleigh distribution called half-logistic Generalized Rayleigh distribution, which has submodels the Generalized Rayleigh and Rayleigh distribution. The proposed model is …

Data clustering is one of the main issues in the optimization problem. It is the process of clustering a group of items into several groups. Items within each group have the greatest similarity and the least similarity to things in other groups.

Agriculture, engineering, public health, sociology, psychology, and epidemiology are just few of the numerous disciplines that find analysis and modeling of zero-truncated count data to be of paramount importance. Very recently, researchers have …

In this paper, we propose the exponential ratio-type estimator for the elevated estimation of population mean, implying one auxiliary variable in stratified random sampling using the conventional ratio and, Bahl and Tuteja exponential ratio-type …

In the era of big data, preserving data privacy has become paramount due to the sheer volume and sensitivity of the information being processed. This research is dedicated to safeguarding data privacy through a novel data sanitization approach …

Panel count data refers to the information collected in studies focusing on recurrent events, where subjects are observed only at specific time points. If these study subjects are exposed to recurrent events of several types, we obtain panel count …

In this research, we introduce an innovative automated resume screening approach that leverages advanced Natural Language Processing (NLP) technology, specifically the Bidirectional Encoder Representations from Transformers (BERT) language model …

Traditionally, in cognitive modeling for binary decision-making tasks, stochastic differential equations, particularly a family of diffusion decision models, are applied. These models suffer from difficulties in parameter estimation and …

This paper introduces a new family of distributions called the hyperbolic tangent (HT) family. The cumulative distribution function of this model is defined using the standard hyperbolic tangent function. The fundamental properties of the …

The main objective of this paper is to forecast the realized volatility (RV) of Bitcoin futures (BTCF) market. To serve our purpose, we propose an augmented heterogenous autoregressive (HAR) model to consider the information on time-varying jumps …

In this paper, we propose and investigate a novel approach for generating the probability distributions. The novel method is known as the SMP transformation technique. By using the SMP Transformation technique, we have developed a new model of the …