In this paper, we will provide a proposed method to estimate missing values for the Explanatory variables for Non-Parametric Multiple Regression Model and compare it with the Imputation Arithmetic mean Method, The basis of the idea of this method was based on how to employ the causal relationship between the variables in finding an efficient estimate of the missing value, we rely on the use of the Kernel estimate by Nadaraya – Watson Estimator , and on Least Squared Cross Validation (LSCV) to estimate the Bandwidth, and we use the simulation study to compare between the two methods.

The research dealt with a comparative study between some semi-parametric estimation methods to the Partial linear Single Index Model using simulation. There are two approaches to model estimation two-stage procedure and MADE to estimate this model. Simulations were used to study the finite sample performance of estimating methods based on different Single Index models, error variances, and different sample sizes , and the mean average squared errors were used as a comparison criterion between the methods were used. The results showed a preference for the two-stage procedure depending on all the cases that were used

The need for a flexible and cost effective biometric security system is the inspired of this paper. Face recognition is a good contactless biometric and it is suitable and applicable for Wireless Sensor Network (WSN). Image processing and image communication is a challenges task in WSN due to the heavy processing and communication that reduce the life time of the network. This paper proposed a face recognition algorithm on WSN depending on the principles of the unique algorithm that hold the capacity of the network to the sink node and compress the communication data to 89.5%. An efficient hybrid method is introduced based upon the advantage of Zak transform to offprint the farthest different features of the face and Eigen face method to

One of the most important features of the Amazon Web Services (AWS) cloud is that the program can be run and accessed from any location. You can access and monitor the result of the program from any location, saving many images and allowing for faster computation. This work proposes a face detection classification model based on AWS cloud aiming to classify the faces into two classes: a non-permission class, and a permission class, by training the real data set collected from our cameras. The proposed Convolutional Neural Network (CNN) cloud-based system was used to share computational resources for Artificial Neural Networks (ANN) to reduce redundant computation. The test system uses Internet of Things (IoT) services th

        In this paper, estimation of system reliability of the multi-components in stress-strength model R_(s,k) is considered, when the stress and strength are independent random variables and follows the Exponentiated Weibull Distribution (EWD) with known first shape parameter θ and, the second shape parameter α is unknown using different estimation methods. Comparisons among the proposed estimators through  Monte Carlo simulation technique were made depend on mean squared error (MSE)  criteria

         Free radical formation in heme proteins is recognized as a factor in mediating the toxicity of many chemicals. The present study was designed to evaluate the dose-response relationship of the free radical scavenging properties of pentoxifylline in nitrite-induced Hb oxidation. Different concentrations of pentoxifylline were added at different time intervals of Hb oxidation in erythrocytes lysate, and formation of methemoglobin (MetHb) was monitored spectrophotometrically. The results showed that in this model, pentoxifylline successfully attenuates Hb oxidation after challenge with sodium nitrite; this protective effect was found to be not related to the catalytic stage of Hb oxidation, th

The tourism industry has become, currently, an art, an industry and a science. It is also one of the components that make up touristic regions. Tourist attractions are no longer the exclusive visits of museums and archeological sites, but also involve other service facilities. It is, therefore, imperative that the authorities should become aware of the degradation of tourist resorts and prevent them from getting worse. Moreover, the authorities should take a set of decisions concerning the protection of the urban aspect with its historical, social, and environmental dimensions, as well as, adapting it to the modern requirements that can bring comfort to the citizens and tourists at physical and psychological levels.

The aim of our study is to solve a nonlinear epidemic model, which is the COVID-19 epidemic model in Iraq, through the application of initial value problems in the current study. The model has been presented as a system of ordinary differential equations that has parameters that change with time. Two numerical simulation methods are proposed to solve this model as suitable methods for solving systems whose coefficients change over time. These methods are the Mean Monte Carlo Runge-Kutta method (MMC_RK) and the Mean Latin Hypercube Runge-Kutta method (MLH_RK). The results of numerical simulation methods are compared with the results of the numerical Runge-Kutta 4th order method (RK4) from 2021 to 2025 using the absolute error, which prove

There are many varied studies that dealt with the dramatic construction, especially books and studies that addressed drama in its construction and the method of writing it, that no textbook or a general cultural content is void of tackling the dramatic text in its construction and how the dramatic action develops in it. Therefore, a question occurs to the mind about the feasibility of dealing with the dramatic construction in this time, where many contemporary studies of dramatology and its relation and the contemporary critical directions are accumulating. This question many have two realistic aspects, yet the novelty and originality that this research shows lie in addressing a refined linguistic text in its style and connotations, such