Wireless Sensor Networks (WSNs) are promoting the spread of the Internet for devices in all areas of
life, which makes it is a promising technology in the future. In the coming days, as attack technologies become
more improved, security will have an important role in WSN. Currently, quantum computers pose a significant
risk to current encryption technologies that work in tandem with intrusion detection systems because it is
difficult to implement quantum properties on sensors due to the resource limitations. In this paper, quantum
computing is used to develop a future-proof, robust, lightweight and resource-conscious approach to sensor
networks. Great emphasis is placed on the concepts of using the BB8

Feature selection (FS) constitutes a series of processes used to decide which relevant features/attributes to include and which irrelevant features to exclude for predictive modeling. It is a crucial task that aids machine learning classifiers in reducing error rates, computation time, overfitting, and improving classification accuracy. It has demonstrated its efficacy in myriads of domains, ranging from its use for text classification (TC), text mining, and image recognition. While there are many traditional FS methods, recent research efforts have been devoted to applying metaheuristic algorithms as FS techniques for the TC task. However, there are few literature reviews concerning TC. Therefore, a comprehensive overview was systematicall

Objective: The evaluation of serum osteocalcin (OSN) for Iraqi infertile patients to see the effect of osteocalcin insufficiency, which may lead to a decreased level of testosterone production in males that may cause infertility. Methods: Forty two newly diagnosed infertile males age range (24–47) years and thirty two apparently healthy males as controls age range (25–58) years. Serum levels of testosterone (TEST), stimulating follicle hormone (FSH) and luteinizing hormone (LH), prolactin (PROL), osteocalcin OSN, and fasting blood sugar (FBS) were performed in both patients and controls. Estimation of serum OSN by Immulite1000 auto-analyzer, TEST, FSH, LH, PROL, and FBS by Immulite2000 auto-analyzer. Results: Infertile patients

The analysis of the classic principal components are sensitive to the outliers where they are calculated from the characteristic values and characteristic vectors of correlation matrix or variance Non-Robust, which yields an incorrect results in the case of these data contains the outliers values. In order to treat this problem, we resort to use the robust methods where there are many robust methods Will be touched to some of them.

   The robust measurement estimators include the measurement of direct robust estimators for characteristic values by using characteristic vectors without relying on robust estimators for the   variance and covariance matrices. Also the analysis of the princ

As the process of  estimate for model and variable selection significant is a crucial process in the semi-parametric modeling At the beginning of the modeling process often At there are many explanatory variables to Avoid the loss of any explanatory elements may be important as a result , the selection of significant variables become necessary , so the process of variable selection is not intended to simplifying  model complexity explanation , and also predicting. In this research was to use some of the semi-parametric methods (LASSO-MAVE , MAVE and The proposal method (Adaptive LASSO-MAVE) for variable selection and estimate semi-parametric single index model (SSIM) at the same time .

In recent decades, tremendous success has been achieved in the advancement of chemical admixtures for Portland cement concrete. Most efforts have concentrated on improving the properties of concrete and studying the factors that influence on these properties. Since the compressive strength is considered a valuable property and is invariably a vital element of the structural design, especially high early strength development which can be provide more benefits in concrete production, such as reducing construction time and labor and saving the formwork and energy. As a matter of fact, it is influenced as a most properties of concrete by several factors including water-cement ratio, cement type and curing methods employed.
Because of acce

The effect of micro-and nano silica particles (silica SiO2 (100 μm), Fused silica (12nm)) on some mechanical properties of epoxy resin was investigated (Young's modulus, Flexural strength). The micro-and nano composites were prepared by using three steps process with different volume fraction of micro-and nano particles (1, 2, 3, 4, 5, 7, 10, 15, and 20 vol. %). Flexural strength and Young's modulus of nano composites were increased at low volume fraction (max. enhancement at 4 vol.% ). However at higher volume fraction both Young's modulus and flexural strength decrease. Moreover, above, the mechanical properties are enhanced more than that of neat epoxy resin. The flexural strength decreases with increasing the volume fraction of micr

Evolutionary algorithms are better than heuristic algorithms at finding protein complexes in protein-protein interaction networks (PPINs). Many of these algorithms depend on their standard frameworks, which are based on topology. Further, many of these algorithms have been exclusively examined on networks with only reliable interaction data. The main objective of this paper is to extend the design of the canonical and topological-based evolutionary algorithms suggested in the literature to cope with noisy PPINs. The design of the evolutionary algorithm is extended based on the functional domain of the proteins rather than on the topological domain of the PPIN. The gene ontology annotation in each molecular function, biological proce

In this research, we studied the multiple linear regression models for two variables in the presence of the autocorrelation problem for the error term observations and when the error is distributed with general logistic distribution. The auto regression model is involved in the studying and analyzing of the relationship between the variables, and through this relationship, the forecasting is completed with the variables as values. A simulation technique is used for comparison methods depending on the mean square error criteria in where the estimation methods that were used are (Generalized Least Squares, M Robust, and Laplace), and for different sizes of samples (20, 40, 60, 80, 100, 120). The M robust method is demonstrated the best metho