This research includes the study of dual data models with mixed random parameters, which contain two types of parameters, the first is random and the other is fixed. For the random parameter, it is obtained as a result of differences in the marginal tendencies of the cross sections, and for the fixed parameter, it is obtained as a result of differences in fixed limits, and random errors for each section. Accidental bearing the characteristic of heterogeneity of variance in addition to the presence of serial correlation of the first degree, and the main objective in this research is the use of efficient methods commensurate with the paired data in the case of small samples, and to achieve this goal, the feasible general least squa

Trimmed Linear moments (TL-moments) are natural generalization of L-moments that do not require the mean of the underlying distribution to exist. It is known that the sample TL-moments is unbiased estimators to corresponding population TL-moment. Since different choices for the amount of trimming give different values of the estimators it is important to choose the estimator that has minimum mean squares error than others. Therefore, we derive an optimal choice for the amount of trimming from known distributions based on the minimum errors between the estimators. Moreover, we study simulation-based approach to choose an optimal amount of trimming and maximum like hood method by computing the estimators and mean squares error for range of

Experimental measurements were done for characterizing current-voltage and power-voltage of two types of photovoltaic (PV) solar modules; monocrystalline silicon (mc-Si) and copper indium gallium di-selenide (CIGS). The conversion efficiency depends on many factors, such as irradiation and temperature. The assembling measures as a rule cause contrast in electrical boundaries, even in cells of a similar kind. Additionally, if the misfortunes because of cell associations in a module are considered, it is hard to track down two indistinguishable photovoltaic modules. This way, just the I-V, and P-V bends' trial estimation permit knowing the electrical boundaries of a photovoltaic gadget with accuracy. This measure

The research aimed to identify the causal relationship between forgiveness and psychological hardness for university students, by answering the following questions: Does forgiveness cause psychological hardiness? Does psychological hardiness cause forgiveness? Is the relationship between the two variables a reciprocal relationship? The research sample consisted of (300) male and female students from the universities of Baghdad and Al-Mustansiriya University. To extract the psychometric properties of the two scales: forgiveness and psychological hardiness, a sample of (50) male and female students employed to repeat the test, making the six connections between the two research variables. To determine the causal relationship, The Pearson c

This research aimed to identify the structural model of the relationship between emotional creativity and self-efficacy among male and female students of the preparatory year at Tabuk University. The current study adopted the descriptive correlational approach, as it is appropriate to the nature of the study. The study tools contained (60) items that measure the relationship between emotional creativity and self-efficacy among the male and female students of the preparatory year at Tabuk University. The study sample was chosen by the stratified random method of the study community, where the study sample reached (183) male and female students of the preparatory year at the University of Tabuk. The results of the study showed that there a

      In this paper fractional Maxwell fluid equation has been solved. The solution is in the Mettag-Leffler form. For  the corresponding solutions for ordinary Maxwell fluid are obtained as limiting case of general solutions. Finally, the effects of different parameters on the velocity and shear stress profile are analyzed through plotting the velocity and shear stress profile.

The objective of this study was tointroduce a recursive least squares (RLS) parameter estimatorenhanced by using a neural network (NN) to facilitate the computing of a bit error rate (BER) (error reduction) during channels estimation of a multiple input-multiple output orthogonal frequency division multiplexing (MIMO-OFDM) system over a Rayleigh multipath fading channel.Recursive least square is an efficient approach to neural network training:first, the neural network estimator learns to adapt to the channel variations then it estimates the channel frequency response. Simulation results show that the proposed method has better performance compared to the conventional methods least square (LS) and the original RLS and it is more robust a

     In this paper, the maximum likelihood estimator and the Bayes estimator of the reliability function for negative exponential distribution has been derived, then a Monte –Carlo simulation technique was employed to compare the performance of such estimators. The integral mean square error (IMSE) was used as a criterion for this comparison. The simulation results displayed that the Bayes estimator performed better than the maximum likelihood estimator for different samples sizes.