Human detection represents a main problem of interest when using video based monitoring. In this paper, artificial neural networks, namely multilayer perceptron (MLP) and radial basis function (RBF) are used to detect humans among different objects in a sequence of frames (images) using classification approach. The classification used is based on the shape of the object instead of depending on the contents of the frame. Initially, background subtraction is depended to extract objects of interest from the frame, then statistical and geometric information are obtained from vertical and horizontal projections of the objects that are detected to stand for the shape of the object. Next to this step, two ty

The question of estimation took a great interest in some engineering, statistical applications, various applied, human sciences, the methods provided by it helped to identify and accurately the many random processes.

In this paper, methods were used through which the reliability function, risk function, and estimation of the distribution parameters were used, and the methods are (Moment Method, Maximum Likelihood Method), where an experimental study was conducted using a simulation method for the purpose of comparing the methods to show which of these methods are competent in practical application This is based on the observations generated from the Rayleigh logarithmic distribution (RL) with sample sizes

The current study aims to compare between the assessments of the Rush model’s parameters to the missing and completed data in various ways of processing the missing data. To achieve the aim of the present study, the researcher followed the following steps: preparing Philip Carter test for the spatial capacity which consists of (20) items on a group of (250) sixth scientific stage students in the directorates of Baghdad Education at Al–Rusafa (1^st, 2^nd and 3^rd) for the academic year (2018-2019). Then, the researcher relied on a single-parameter model to analyze the data. The researcher used Bilog-mg3 model to check the hypotheses, data and match them with the model. In addition

Analysis the economic and financial phenomena and other requires to build the appropriate model, which represents the causal relations between factors. The operation building of the model depends on Imaging conditions and factors surrounding an in mathematical formula and the Researchers target to build that formula appropriately. Classical linear regression models are an important statistical tool, but used in a limited way, where is assumed that the relationship between the variables illustrations and response variables identifiable. To expand the representation of relationships between variables that represent the phenomenon under discussion we used Varying Coefficient Models

Most of the Weibull models studied in the literature were appropriate for modelling a continuous random variable which assumes the variable takes on real values over the interval [0,∞]. One of the new studies in statistics is when the variables take on discrete values. The idea was first introduced by Nakagawa and Osaki, as they introduced discrete Weibull distribution with two shape parameters q and β where      0 < q < 1 and b > 0. Weibull models for modelling discrete random variables assume only non-negative integer values. Such models are useful for modelling for example; the number of cycles to failure when components are subjected to cyclical loading. Discrete Weibull models can be obta

Abstract 

The Phenomenon of Extremism of Values ​​(Maximum or Rare Value) an important phenomenon is the use of two techniques of sampling techniques to deal with this Extremism: the technique of the peak sample and the maximum annual sampling technique (AM) (Extreme values, Gumbel) for sample (AM) and (general Pareto, exponential) distribution of the POT sample. The cross-entropy algorithm was applied in two of its methods to the first estimate using the statistical order and the second using the statistical order and likelihood ratio. The third method is proposed by the researcher. The MSE comparison coefficient of the estimated parameters and the probability density function for each of the distributions were

In this research, the focus was on estimating the parameters on (min- Gumbel distribution), using the maximum likelihood method and the Bayes method. The genetic algorithmmethod was employed in estimating the parameters of the maximum likelihood method as well as  the Bayes method. The comparison was made using the mean error squares (MSE), where the best  estimator  is the one who has the least mean squared error. It was noted that the best estimator was (BLG_GE).

Abstract:

 This research aims to compare Bayesian Method and Full Maximum Likelihood to estimate hierarchical Poisson regression model.

The comparison was done by  simulation  using different sample sizes (n = 30, 60, 120) and different Frequencies (r = 1000, 5000) for the experiments as was the adoption of the  Mean Square Error to compare the preference estimation methods and then choose the best way to appreciate model and concluded that hierarchical Poisson regression model that has been appreciated Full Maximum Likelihood Full Maximum Likelihood  with sample size  (n = 30) is the best to represent the maternal mortality data after it has been reliance value param

The stanza in the sonnet has been defined as a set of poetic lines followed after proem
and be the same meter as that of proem in complete stanza, but in rhyme scheme different
from that meter. The couplet is defined as set of poetic lines that followed the stanza and be as
the same meter as that of stanza, but with different rhyme scheme. This definition is approved
by all specialized in field of Andalus literature and it was also proven to them that this
construction emptied of indications. This meter has endeavored to prove that that there were a
difference in denotation for meaning between the stanza and couplet. Thus, the sonneteers
have outweighed the sonnet of the blind "Tutaili" to their sonnets as they felt

Carbon nanotubes (CNTs) were synthesized via liquefied petroleum gas (LPG) as precursor using flame fragments deposition (FFD) technique. In vitro, biological activates of carbon nanotubes (CNTs) synthesized by FFD technique were investigated. The physiochemical characterizations of synthesized CNTs are similar to other synthesized CNTs and to the standard sample. Pharmaceutical application of synthesized CNTs was studied via conjugation and adsorption with different types of medicines as promote groups. The conjugation of CNTs was performed by adsorption the drugs such as sulfamethoxazole (SMX) and trimethoprim (TMP) on CNTs depending on physical properties of both bonded parts. The synthesized CNTs almost have the same performance in a