The aim of the research is to estimate the hidden population. Here، the number of drug users in Baghdad was calculated for the male age group (15-60) years old ، based on the Bayesian models. These models are used to treat some of the bias in the Killworth method Accredited in many countries of the world.

Four models were used: random degree، Barrier effects، Transmission bias، the first model being random، an extension of the Killworth model، adding random effects such as variance and uncertainty Through the size of the personal network، and when expanded by adding the fact that the respondents have different tendencies، the mixture of non-random variables with random to produce

The notion of a Tˉ-pure sub-act and so Tˉ-pure sub-act relative to sub-act are introduced. Some properties of these concepts have been studied.

The aim of the thesis is to estimate the partial and inaccessible population groups, which is a field study to estimate the number of drug’s users in the Baghdad governorate for males who are (15-60) years old.

Because of the absence of data approved by government institutions, as well as the difficulty of estimating the numbers of these people from the traditional survey, in which the respondent expresses himself or his family members in some cases. In these challenges, the NSUM Network Scale-Up Method Is mainly based on asking respondents about the number of people they know in their network of drug addicts.

Based on this principle, a statistical questionnaire was designed to

A new Species of the Cerambycinae belonging to the genus Hesperophanes was found new to the fauna of Iraq and Science. H. testaceus was studied in details and the male genitalia were illustrated. Type's paratypes and the locality of this newly described Species were mentioned.

This work focuses on the preparation of pure nanocrystalline SnO2 and SnO2:Cu thin films on cleaned glass substrates utilizing a sol-gel spin coating and chemical bath deposition (CBD) procedures. The primary aim of this study is to investigate the possible use of these thin films in the context of gas sensor applications. The films underwent annealing in an air environment at a temperature of 500 ^◦C for duration of 60 minutes. The thickness of the film that was deposited may be estimated to be around 300 nm. The investigation included an examination of the structural, optical, electrical, and sensing characteristics, which were explored across various preparation circumstances, specifically focusing on varied

An electrochemical sensor based on an amino-functionalized iron NH2-MIL-101(Fe) metal-organic framework (MOF)/Pd nanoparticles (NPs) composite-modified screen-printed elec­trode (SPE) is prepared for the simultaneous determination of norepinephrine (NEPI) and acetaminophen (ACP). The NH2-MIL-101(Fe) MOF/Pd NPs/SPE electrochemical sensor shows a significant enhancement in the response peak current of NEPI, as compared to bare SPE. This suggests that the unique features of NH2-MIL-101(Fe) MOF/Pd NPs composite-mo­di­fied SPE improve the electro­catalytic oxidation of NEPI. Such a synergistic effect bet­ween NH2-MIL-101(Fe) MOF and Pd NPs results in a significant enhancement in the res­pon­se, where the MOF's high surface area co

In this paper, author’s study sub diffusion bio heat transfer model and developed explicit finite difference scheme for time fractional sub diffusion bio heat transfer equation by using caputo fabrizio fractional derivative. Also discussed conditional stability and convergence of developed scheme. Furthermore numerical solution of time fractional sub diffusion bio heat transfer equation is obtained and it is represented graphically by Python.

Facial emotion recognition finds many real applications in the daily life like human robot interaction, eLearning, healthcare, customer services etc. The task of facial emotion recognition is not easy due to the difficulty in determining the effective feature set that can recognize the emotion conveyed within the facial expression accurately. Graph mining techniques are exploited in this paper to solve facial emotion recognition problem. After determining positions of facial landmarks in face region, twelve different graphs are constructed using four facial components to serve as a source for sub-graphs mining stage using gSpan algorithm. In each group, the discriminative set of sub-graphs are selected and fed to Deep Belief Network (DBN) f