Abstract-Servo motors are important parts of industry automation due to their several advantages such as cost and energy efficiency, simple design, and flexibility. However, the position control of the servo motor is a difficult task because of different factors of external disturbances, nonlinearities, and uncertainties. To tackle these challenges, an adaptive integral sliding mode control (AISMC) is proposed, in which a novel bidirectional adaptive law is constructed to reduce the control chattering. The proposed control has three steps to be designed. Firstly, a full-order integral sliding manifold is designed to improve the servo motor position tracking performance, in which the reaching phase is eliminated to achieve the invariance of

   The Financial systems can be classified into two types. The first is the market–oriented, which is applied in United States and United Kingdom. While the second is bank-oriented as in Japan and Germany.

   This study tries to explain the reasons which make some countries adopt the first one instead of the second, and the contrary. So the study consists of three sections. The first deals with the concept of financial system and it are functions. The second displays the indicators which are used to classify the financial systems, while the third one is devoted to the factors that determine the type of financial system .These sections followed by some conclusions.

A multivariate multisite hydrological data forecasting model was derived and checked using a case study. The philosophy is to use simultaneously the cross-variable correlations, cross-site correlations and the time lag correlations. The case study is of two variables, three sites, the variables are the monthly rainfall and evaporation; the sites are Sulaimania, Dokan, and Darbandikhan.. The model form is similar to the first order auto regressive model, but in matrices form. A matrix for the different relative correlations mentioned above and another for their relative residuals were derived and used as the model parameters. A mathematical filter was used for both matrices to obtain the elements. The application of this model indicates i

The calculation of potential earth's surface solar radiation is imperative for analyzing the atmosphere-vegetation-soil interaction process. Therefore, many schemes were introduced with  direct (using net radiometer) or indirect (using air temperature or air plus soil temperatures) formulas. Three combinations of factors are known to control the R_n value; the astronomical based factors which determine the general spatial distribution of R_n values, the climatological factors which determine the assigned spatial variation of those values, and the topographical factors that influence climatological factors rates ( i.e. have indirect effects on Rn values).

     For Iraq, the ecosystem in

The ground state proton momentum distributions (PMD) and elastic charge form
factors for some odd 1f  2p shell nuclei, such as , , 59 63Co Cu and Cu 65 have been
studied using the Coherent Density Fluctuation Model and formulated by means of
the fluctuation function (weight function) ( ) .
2
f x The fluctuation function has been
connected to the charge density distribution of the nuclei and determined from the
theory and experiment result. The feature of the long-tail behavior at high
momentum region of the PMD has been calculated by both the theoretical and
experimental fluctuation functions. It is found that the inclusion of the quadrupole
form factors ( ) 2 F q C in all nuclei under study, which are de

Coherent density fluctuation model (CDFM) has been used to calculate the
proton momentum distributions (PMD) and elastic electron scattering form factors,
F(q), of the ground state for some even mass nuclei of fp-shell, such as 52Cr, 58Fe and
64Ni nuclei. Both of the PMD and F(q) have been expressed in terms of the weight
function ( ( ) )
2
f x which is determined by means of the charge density
distributions (CDD) of the nuclei and determined from theory and experiment. The
feature of the long-tail behavior at high momentum region of the PMD’s has been
obtained by both the theoretical and experimental weight functions. The calculated
form factors of these nuclei are in reasonable agreement with those of th

Aerial Robot Arms (ARAs) enable aerial drones to interact and influence objects in various environments. Traditional ARA controllers need the availability of a high-precision model to avoid high control chattering. Furthermore, in practical applications of aerial object manipulation, the payloads that ARAs can handle vary, depending on the nature of the task. The high uncertainties due to modeling errors and an unknown payload are inversely proportional to the stability of ARAs. To address the issue of stability, a new adaptive robust controller, based on the Radial Basis Function (RBF) neural network, is proposed. A three-tier approach is also followed. Firstly, a detailed new model for the ARA is derived using the Lagrange–d’A

The use of Bayesian approach has the promise of features indicative of regression analysis model classification tree to take advantage of the above information by, and ensemble trees for explanatory variables are all together and at every stage on the other. In addition to obtaining the subsequent information at each node in the construction of these classification tree. Although bayesian estimates is generally accurate, but it seems that the logistic model is still a good competitor in the field of binary responses through its flexibility and mathematical representation. So is the use of three research methods data processing is carried out, namely: logistic model, and model classification regression tree, and bayesian regression tree mode

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