The main objective of this paper is to designed algorithms and implemented in the construction of the main program designated for the determination the tenser product of representation for the special linear group.

The most important topic for psychologist generally is factor of education and it's active tools because learning needs active perception for stimulus that recived by the educator and give it avalue and meaning , Need for cognition is
very important in the various daily fields of life , especially in learning and teaching and the academy work , it help with shifting the learning level for people , and icreas the intense and challenge between them
The research endeavored to achieve the following aim :
1- Measuring the level of peripheral perception for the university student .
2- Measuring the level of need for cognition for the university student .
3- Measuring the level of peripheral perception for the university student

The aim of the research is to study the comparison between (ARIMA) Auto Regressive Integrated Moving Average and(ANNs) Artificial Neural Networks models and to select the best one for prediction the monthly relative humidity values depending upon the standard errors between estimated and observe values . It has been noted that both can be used for estimation and the best on among is (ANNs) as the values (MAE,RMSE, R2) is )0.036816,0.0466,0.91) respectively for the best formula for model (ARIMA) (6,0,2)(6,0,1) whereas the values of estimates relative to model (ANNs) for the best formula (5,5,1) is (0.0109, 0.0139 ,0.991) respectively. so that model (ANNs) is superior than (ARIMA) in a such evaluation.

We propose a novel strategy to optimize the test suite required for testing both hardware and software in a production line. Here, the strategy is based on two processes: Quality Signing Process and Quality Verification Process, respectively. Unlike earlier work, the proposed strategy is based on integration of black box and white box techniques in order to derive an optimum test suite during the Quality Signing Process. In this case, the generated optimal test suite significantly improves the Quality Verification Process. Considering both processes, the novelty of the proposed strategy is the fact that the optimization and reduction of test suite is performed by selecting only mutant killing test cases from cumulating t-way test ca

ABSTRUCT

In This Paper, some semi- parametric spatial models were estimated, these models are, the semi – parametric spatial error model (SPSEM), which suffer from the problem of spatial errors dependence, and the semi – parametric spatial auto regressive model (SPSAR). Where the method of maximum likelihood was used in estimating the parameter of spatial error          ( λ ) in the model (SPSEM), estimated  the parameter of spatial dependence ( ρ ) in the model ( SPSAR ), and using the non-parametric method in estimating the smoothing function m(x) for these two models, these non-parametric methods are; the local linear estimator (LLE) which require finding the smoo

Hypothesis CO2 geological storage (CGS) involves different mechanisms which can store millions of tonnes of CO2 per year in depleted hydrocarbon reservoirs and deep saline aquifers. But their storage capacity is influenced by the presence of different carboxylic compounds in the reservoir. These molecules strongly affect the water wetness of the rock, which has a dramatic impact on storage capacities and containment security. However, precise understanding of how these carboxylic acids influence the rock’s CO2-wettability is lacking. Experiments We thus systematically analysed these relationships as a function of pressure, temperature, storage depth and organic acid concentrations. A particular focus was on identifying organic acid conce

Early diagnosis and clinical decision-making depend on accurate brain tumor classification using magnetic resonance imaging (MRI). However, traditional deep learning methods usually rely on centralized medical data, which raises privacy concerns and limits the use of distributed clinical data. This research proposes a privacy-preserving federated learning framework for MRI image-based binary brain tumor classification using a decentralized ResNet-18 architecture that enables collaborative training without sharing raw patient data. To reflect realistic clinical conditions, the framework integrates heterogeneous multi-source datasets in different image formats (PNG and JPG) and evaluates performance under both IID and non-IID settings

In this work, plasma parameters such as, the electron temperature )Te(, electron density ne, plasma frequency )fp(, Debye length )λD(
and Debye number )ND), have been studied using optical emission spectroscopy technique. The spectrum of plasma with different values of energy, Pb doped CuO at different percentage (X=0.6, 0.7, 0.8) were recorded. The spectroscopic study for these mixing under vacuum with pressure down to P=2.5×10-2 mbar. The results of electron temperature for X=0.6 range (1.072-1.166) eV, for X=0.7 the Te range (1.024-0.855) eV and X=0.8 the Te is (1.033-0.921) eV. Optical properties of CuO:Pb thin films were determined through the optical transmission method using ultraviolet visible spectrophotometer within the ra

 In this work, plasma parameters such as (electron temperature (Te), electron density (ne), plasma frequency (fp) and Debye length (λD)) were studied using spectral analysis techniques. The spectrum of the plasma was recorded with different energy values, SnO2 and ZnO anesthetized at a different ratio (X = 0.2, 0.4 and 0.6) were recorded. Spectral study of this mixing in the air. The results showed electron density and electron temperature increase in zinc oxide: tin oxide alloy targets. It was located  that  The intensity of the lines increases in different laser peak powers when the laser peak power increases and then decreases when the force continues to increase.