The main purpose from this paper is to introduce a new kind of soft open sets in soft
topological spaces called soft omega open sets and we show that the collection of
every soft omega open sets in a soft topological space (X,~,E) forms a soft topology
  ~
on X which is soft finer than  ~
. Moreover we use soft omega open sets to define
and study new classes of soft functions called weakly soft omega open functions and
weakly soft omega closed functions which are weaker than weakly soft open functions
and weakly soft closed functions respectively. We obtain their basic properties, their
characterizations, and their relationships with other kinds of soft functions between
soft topological spaces.<

In these notes, our goal is to give some results on criterion for complex analytic map-germs by their tangent spaces with respect to -equivalence where is the module of complex analytic vector fields on .In addition, we give some results about -trivial analytic family, the direct product and direct sum of map-germs.

Tow   results  are  proved.  The  first  gives necessary  and   ullicient

conditions for a permutation group to have the prope1ty that each of its rational - valued character can be written as (integral) linear combination of characters induced from the principal characters of certain subgroup. The mher presents that this property is extendable to direct product of groups.

Examples give.

In this paper, we presented new types of Mc-function by using 𝜔-open and 𝑁-open sets some of them are weaker than Mc-function and some are stronger, which are 𝜔Mc-function, M𝜔c-function, 𝜔M𝜔c-function, 𝑁Mc-function, M𝑁c-function and 𝑁M𝑁c-function, also we submitted new kinds of continuous functions and compact functions and we illustrated the relationships between these types. The purpose of this paper is to expand the study of Mcfunction and to get results that we need to find the relationship with the types that have been introduced.

Intended for getting good estimates with more accurate results, we must choose the appropriate method of estimation. Most of the equations in classical methods are linear equations and finding analytical solutions to such equations is very difficult. Some estimators are inefficient because of problems in solving these equations. In this paper, we will estimate the survival function of censored data by using one of the most important artificial intelligence algorithms that is called the genetic algorithm to get optimal estimates for parameters Weibull distribution with two parameters. This leads to optimal estimates of the survival function. The genetic algorithm is employed in the method of moment, the least squares method and the weighted

The aim of this paper is to present a weak form of -light functions by using -open set which is -light function, and to offer new concepts of disconnected spaces and totally disconnected spaces. The relation between them have been studied. Also, a new form of -totally disconnected and inversely -totally disconnected function have been defined, some examples and facts was submitted.

The Log-Logistic distribution is one of the important statistical distributions as it can be applied in many fields and biological experiments and other experiments, and its importance comes from the importance of determining the survival function of those experiments. The research will be summarized in making a comparison between the method of maximum likelihood and the method of least squares and the method of weighted least squares to estimate the parameters and survival function of the log-logistic distribution using the comparison criteria MSE, MAPE, IMSE, and this research was applied to real data for breast cancer patients. The results showed that the method of Maximum likelihood best in the case of estimating the paramete

In this paper, the maximum likelihood estimates for parameter ( ) of two parameter's Weibull are studied, as well as white estimators and (Bain & Antle) estimators, also Bayes estimator for scale parameter ( ), the simulation procedures are used to find the estimators and comparing between them using MSE. Also the application is done on the data for 20 patients suffering from a headache disease.

In this paper, we derived an estimators and parameters of Reliability and Hazard function of new mix distribution ( Rayleigh- Logarithmic) with two parameters and increasing failure rate using Bayes Method with Square Error Loss function and Jeffery and conditional probability random variable of observation. The main objective of this study is to find the efficiency of the derived of Bayesian estimator compared to the to the Maximum Likelihood of this function using Simulation technique by Monte Carlo method under different Rayleigh- Logarithmic parameter and sample sizes. The consequences have shown that Bayes estimator has been more efficient than the maximum likelihood estimator in all sample sizes with application

       Th  goal of the pr s nt p p r is to obt in some differ tial sub rdin tion an  sup r dination the rems for univalent functions related b  differential operator  Also, we discussed some sandwich-type results.