In this study, we made a comparison between LASSO & SCAD methods, which are two special methods for dealing with models in partial quantile regression. (Nadaraya & Watson Kernel) was used to estimate the non-parametric part ;in addition, the rule of thumb method was used to estimate the smoothing bandwidth (h). Penalty methods proved to be efficient in estimating the regression coefficients, but the SCAD method according to the mean squared error criterion (MSE) was the best after estimating the missing data using the mean imputation method

In data mining, classification is a form of data analysis that can be used to extract models describing important data classes. Two of the well known algorithms used in data mining classification are Backpropagation Neural Network (BNN) and Naïve Bayesian (NB). This paper investigates the performance of these two classification methods using the Car Evaluation dataset. Two models were built for both algorithms and the results were compared. Our experimental results indicated that the BNN classifier yield higher accuracy as compared to the NB classifier but it is less efficient because it is time-consuming and difficult to analyze due to its black-box implementation.

Today, the role of cloud computing in our day-to-day lives is very prominent. The cloud computing paradigm makes it possible to provide demand-based resources. Cloud computing has changed the way that organizations manage resources due to their robustness, low cost, and pervasive nature. Data security is usually realized using different methods such as encryption. However, the privacy of data is another important challenge that should be considered when transporting, storing, and analyzing data in the public cloud. In this paper, a new method is proposed to track malicious users who use their private key to decrypt data in a system, share it with others and cause system information leakage. Security policies are also considered to be int

Modern civilization increasingly relies on sustainable and eco-friendly data centers as the core hubs of intelligent computing. However, these data centers, while vital, also face heightened vulnerability to hacking due to their role as the convergence points of numerous network connection nodes. Recognizing and addressing this vulnerability, particularly within the confines of green data centers, is a pressing concern. This paper proposes a novel approach to mitigate this threat by leveraging swarm intelligence techniques to detect prospective and hidden compromised devices within the data center environment. The core objective is to ensure sustainable intelligent computing through a colony strategy. The research primarily focusses on the

      Cloud computing is an interesting technology that allows customers to have convenient, on-demand network connectivity based on their needs with minimal maintenance and contact between cloud providers. The issue of security has arisen as a serious concern, particularly in the case of cloud computing, where data is stored and accessible via the Internet from a third-party storage system. It is critical to ensure that data is only accessible to the appropriate individuals and that it is not stored in third-party locations. Because third-party services frequently make backup copies of uploaded data for security reasons, removing the data the owner submits does not guarantee the removal of the data from the cloud. Cloud data storag

In this work, we give an identity that leads to establishing the operator . Also, we introduce the polynomials . In addition, we provide Operator proof for the generating function with its extension and the Rogers formula for . The generating function with its extension and the Rogers formula for the bivariate Rogers-Szegö polynomials  are deduced. The Rogers formula for  allows to obtain the inverse linearization formula for , which allows to deduce the inverse linearization formula for . A solution to a q-difference equation is introduced and the solution is expressed in terms of the operators . The q-difference method is used to recover an identity of the operator  and the generating function for the polynomials

with an organized propaganda campaign. This military campaign was helped to formulate its speech by many institutions, research centers, and knowledge and intelligence circles in order to mobilize public opinion gain supporters and face the opponents by different means depending on a variety of styles to achieve its required effects. 
          After the US occupation of Iraq, US media fighters sought to influence the Iraqi public opinion and making them convinced them of the important presence of US military forces in Iraq which necessitated finding its justification through the use of persuasive techniques in its intensive propaganda campaigns. 
  This research discusses the most important

In this work , the ligand [N-(4-Methoxybenzoyl amino)-thioxomethyl] Methionine acid  has been synthesized by the reaction of 4- Methoxybenzoyl isothiocyanate with methionine acid . The metal complexes were prepared through the reaction of metals chlorides of Co(II) , Ni(II), Cu(II), Zn(II) and Cd(II) in ethanol as solvent . The ligand (MbM) and its metal complexes have been characterized by elemental analysis (CHNS), IR, 1H-13CNMR and UV- Vis spectra, magnetic susceptibility measurements, molar conductivity, melting points and atomic absorption. The metal-ligand ratio was determined by mole ratio method. The suggested structures for the Co(II), Ni(II), Cd(II) and Zn(II) complexes are tetrahedral geometry and  the Cu(II) complex

TEOS aerogel a is the most commonly used. a Aerogel has attracted increasing attention from both academic and industries due to its extraordinary performance and potentials. We have systematically studied the relationship between the densification temperature of the synthesis environment of silica aerogels on their resulting morphological, optical and thermal properties. SEM and BET measurements were employed as structural probes to ascertain the structural differences. Lee's disc apparatus was used for determining the thermal conductivity coefficient. There is a systematic correlation between the annealing temperature and the aerogel surface area, porosity, as well as pore size. The implemented autoclave was able to produce aerogel mono

  In this work, nanostructured TiO2 thin films were grown by pulsed laser deposition (PLD) technique on glass substrates. TiO2 thin films then were annealed at 400-600 °C in air for a period of 2 hours. Effect of annealing on the structural and morphological were studied. Many growth parameters have been considered to specify the optimum conditions, namely substrate temperature (300 °C), oxygen pressure (10-2 Torr), laser fluence energy density (0.4 J/cm2), using double frequency Q-switching Nd:YAG laser beam (wavelength 532nm), repetition rate  (1-6 Hz) and the pulse duration of 10 ns. The results of the X-ray test show that all nanostructures tetragonal are polycrystalline. These results show that grain size increase fr