The aim of this research is to identify the impact of the effectiveness of digital transformation technology in improving the efficiency of the insurance service in the public insurance companies in Iraq through digital transformation technology in the insurance process "promotion of the insurance product, submission of insurance application, underwriting, settlement of losses" and to achieve this goal a questionnaire was designed A survey distributed in the surveyed community Which represents the decision makers in the researched companies under study, and one of the most important results of the research was the existence of a relationship between digital transformation and improving the efficiency of the insurance process, whether thr

This paper study two stratified quantile regression models of the marginal and the conditional varieties. We estimate the quantile functions of these models by using two nonparametric methods of smoothing spline (B-spline) and kernel regression (Nadaraya-Watson). The estimates can be obtained by solve nonparametric quantile regression problem which means minimizing the quantile regression objective functions and using the approach of varying coefficient models. The main goal is discussing the comparison between the estimators of the two nonparametric methods and adopting the best one between them

Recently, wireless communication environments with high speeds and low complexity have become increasingly essential. Free-space optics (FSO) has emerged as a promising solution for providing direct connections between devices in such high-spectrum wireless setups. However, FSO communications are susceptible to weather-induced signal fluctuations, leading to fading and signal weakness at the receiver. To mitigate the effects of these challenges, several mathematical models have been proposed to describe the transition from weak to strong atmospheric turbulence, including Rayleigh, lognormal, Málaga, Nakagami-m, K-distribution, Weibull, Negative-Exponential, Inverse-Gaussian, G-G, and Fisher-Snedecor F distributions. This paper extensive

In this paper, a fusion of K models of full-rank weighted nonnegative tensor factor two-dimensional deconvolution (K-wNTF2D) is proposed to separate the acoustic sources that have been mixed in an underdetermined reverberant environment. The model is adapted in an unsupervised manner under the hybrid framework of the generalized expectation maximization and multiplicative update algorithms. The derivation of the algorithm and the development of proposed full-rank K-wNTF2D will be shown. The algorithm also encodes a set of variable sparsity parameters derived from Gibbs distribution into the K-wNTF2D model. This optimizes each sub-model in K-wNTF2D with the required sparsity to model the time-varying variances of the sources in the s

Drip irrigation is one of the conservative irrigation techniques since it implies supplying water directly on the soil through the emitter; it can supply water and fertilizer directly into the root zone. An equation to estimate the wetted area in unsaturated soil is taking into calculating the water absorption by roots is simulated numerically using HYDRUS (2D/3D) software. In this paper, HYDRUS comprises analytical types of the estimate of different soil hydraulic properties. Used one soil type, sandy loam, with three types of crops; (corn, tomato, and sweet sorghum), different drip discharge, different initial soil moisture content was assumed, and different time durations. The relative error for the different hydrauli

The support vector machine, also known as SVM, is a type of supervised learning model that can be used for classification or regression depending on the datasets. SVM is used to classify data points by determining the best hyperplane between two or more groups. Working with enormous datasets, on the other hand, might result in a variety of issues, including inefficient accuracy and time-consuming. SVM was updated in this research by applying some non-linear kernel transformations, which are: linear, polynomial, radial basis, and multi-layer kernels. The non-linear SVM classification model was illustrated and summarized in an algorithm using kernel tricks. The proposed method was examined using three simulation datasets with different sample

Videogames are currently one of the most widespread means of digital communication and entertainment; their releases are attracting considerable interest with growing number of audience and revenues each year. Videogames are examined by a variety of disciplines and fields. Nevertheless, scholarly attention concerned with the discourse of videogames from a linguistic perspective is relatively scarce, especially from a pragma-stylistic standpoint. This book addresses this vital issue by providing a pragma-stylistic analysis of the digital discourse of two well-known action videogames (First Person Shooter Games). It explores the role of the digital discourse of action videogames in maintaining real-like interactivity between the game and the

Objective: To determine the correlation between the second derivative of digital pulse wave and the QT variability index. Method: The cross-sectional study was conducted from October 2021 to May 2022 at the Department of Physiology, College of Medicine, University of Mustansiriyah, Baghdad, Iraq, and comprised healthy women. Samples were raised by simple random technique. Digital pulse waves were captured using a fingertip pulse wave transducer. Lab Chart Pro version 7.2 was used to automatically detect and quantify the amplitude of A, B, C, D and E waves expressed by the second derivative. QT interval of each beat was recorded by electrocardiogram, and was calculated automatically via Lab chart Pro version 7.2 without averaging. D