Vagrancy is global problem, but its geographical distribution differs from one society
to another and from one place to another inside the same society.Till now there isn't a real factor that can explain the phenomenon, spite that economy plays aconstituent and distinguishing part, and spite the fact that Vagrancy is considered a realdeviation that can be compared with criminality level, and cannot be separated from its effecton family, local society and school. In addition to unprecedented work under heavily pressurethat attack to a minimum protection and safety. Vagrant may be a child, a teen, a young, or
even an old man. Vagrancy thus means different people with different ages and not onlyprecisely children. Vagrant is not necessary to be a male, in modern societies the differencesbetween male and female get back to make a female vagrant as well as male but in a lower proportion compared with the female this because of some traditional controls. The main reason behind vagrancy is that family environment that has its pressures, while street has its attractive features. Inside family, poverty deprivation, drinking alcohol, cannabis, family
violence and multi-wives ….. etc. In the street there is freedom of walking, getting foodthrough begging, far away from father stick or mother complain, inside family there is
isolation, while on the street there is an open way through it there is multi elements of threat
to the vagrant life, personality and future. Vagrant world is not easy, it's in the bottom of society it like a forest full of violence and the principles of shame and cooperation collapse.
Many academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Deci
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The notion of interval value fuzzy k-ideal of KU-semigroup was studied as a generalization of afuzzy k-ideal of KU-semigroup. Some results of this idea under homomorphism are discussed. Also, we presented some properties about the image (pre-image) for interval~ valued fuzzy~k-ideals of a KU-semigroup. Finally, the~ product of~ interval valued fuzzyk-ideals is established.
Given a matrix, the Consecutive Ones Submatrix (C1S) problem which aims to find the permutation of columns that maximizes the number of columns having together only one block of consecutive ones in each row is considered here. A heuristic approach will be suggested to solve the problem. Also, the Consecutive Blocks Minimization (CBM) problem which is related to the consecutive ones submatrix will be considered. The new procedure is proposed to improve the column insertion approach. Then real world and random matrices from the set covering problem will be evaluated and computational results will be highlighted.
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Many academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Decision Tre
... Show MoreA- The research problem: the research problem which is the garments industry, as a
whole it does not rely on a single system in the sizes of the clothing and the working
companies, see that it is not plausible that the sizes be unificd and consistent in all companies.
The current sizes in the domestic Iraqi markets are not suitable for some females ,on the other
hand the Iraqi industry suffers the lack of a modern standard for some Iraqis female bodies.
B- The Signifiance of the research: lies in the study of the diversity of the human body
sizes and naming them to reflect the desires and requirements of the consumer and try to find
a method to meet their expectations as well as to raise the level of garments industr
Maximum likelihood estimation method, uniformly minimum variance unbiased estimation method and minimum mean square error estimation, as classical estimation procedures, are frequently used for parameter estimation in statistics, which assuming the parameter is constant , while Bayes method assuming the parameter is random variable and hence the Bayes estimator is an estimator which minimize the Bayes risk for each value the random observable and for square error lose function the Bayes estimator is the posterior mean. It is well known that the Bayesian estimation is hardly used as a parameter estimation technique due to some difficulties to finding a prior distribution.
The interest of this paper is that
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