The aim of this research is to investigate the effect of economic, social and institutional factors on adoption within the national program for the propagation of high-rank seeds of wheat crop. 170 questionnaires were collected, 50% of them were participants in the program from Wasit and Babil governorates. Probabilistic regression models were used to know this effect, and the possibility of adopting Farmers of improved seeds produced from the national program for the multiplication of seeds of higher grades using the (ADOPT) program. The adoption rate was 0.12%, and the total number of adopters were 12 farmers, at a rate of 14.2%. Tobit model was estimated  to find out the impact of the profitability of the dunum, capital, farm si

In order to obtain a mixed model with high significance and accurate alertness, it is necessary to search for the method that performs the task of selecting the most important variables to be included in the model, especially when the data under study suffers from the problem of multicollinearity as well as the problem of high dimensions. The research aims to compare some methods of choosing the explanatory variables and the estimation of the parameters of the regression model, which are Bayesian Ridge Regression (unbiased) and the adaptive Lasso regression model, using simulation. MSE was used to compare the methods.

Purpose: To use the L25 Taguchi orthogonal array for optimizing the three main solvothermal parameters that affect the synthesis of metal-organic frameworks-5 (MOF-5). Methods: The L25 Taguchi methodology was used to study various parameters that affect the degree of crystallinity (DOC) of MOF-5. The parameters comprised temperature of synthesis, duration of synthesis, and ratio of the solvent, N,N-dimethyl formamide (DMF) to reactants. For each parameter, the volume of DMF was varied while keeping the weight of reactants constant. The weights of 1,4-benzodicarboxylate (BDC) and Zn(NO3)2.6H2O used were 0.390 g and 2.166 g, respectively. For each parameter investigated, five different levels were used. The MOF-5 samples were synthesi

In light of the development in computer science and modern technologies, the impersonation crime rate has increased. Consequently, face recognition technology and biometric systems have been employed for security purposes in a variety of applications including human-computer interaction, surveillance systems, etc. Building an advanced sophisticated model to tackle impersonation-related crimes is essential. This study proposes classification Machine Learning (ML) and Deep Learning (DL) models, utilizing Viola-Jones, Linear Discriminant Analysis (LDA), Mutual Information (MI), and Analysis of Variance (ANOVA) techniques. The two proposed facial classification systems are J48 with LDA feature extraction method as input, and a one-dimen

Several previous investigations and studies utilized silica fume (SF) or (micro silica) particles as supplementary cementitious material added as a substitute to cement-based mortars and their effect on the overall properties, especially on physical properties, strength properties, and mechanical properties. This study investigated the impact of the inclusion of silica fume (SF) particles on the residual compressive strengths and microstructure properties of cement-based mortars exposed to severe conditions of elevated temperatures. The prepared specimens were tested and subjected to 25, 250, 450, 600, and 900 °C. Their residual compressive strengths and microstructure were evaluated and compared with control samples (C

The biometric-based keys generation represents the utilization of the extracted features from the human anatomical (physiological) traits like a fingerprint, retina, etc. or behavioral traits like a signature. The retina biometric has inherent robustness, therefore, it is capable of generating random keys with a higher security level compared to the other biometric traits. In this paper, an effective system to generate secure, robust and unique random keys based on retina features has been proposed for cryptographic applications. The retina features are extracted by using the algorithm of glowworm swarm optimization (GSO) that provides promising results through the experiments using the standard retina databases. Additionally, in order t