In this research want to make analysis for some indicators and it's classifications that related with the teaching process and the            scientific level for graduate studies in the university by using analysis of variance for ranked data for repeated measurements instead of the ordinary analysis of variance . We reach many conclusions  for the                         

important classifications for each indicator that has affected on   the teaching process.         &nb

Mansuriya Gas field is an elongated anticlinal structure aligned from NW to SE, about 25 km long and 5-6 km wide. Jeribe formation is considered the main reservoir where it contains condensate fluid and has a uniform thickness of about 60 m. The reservoir is significantly over-pressured, (TPOC, 2014).

This research is about well logs analysis, which involves the determination of Archie petrophysical parameters, water saturation, porosity, permeability and lithology. The interpretations and cross plots are done using Interactive Petrophysics (IP) V3.5 software.

The rock parameters (a, m and n) values are important in determining the water saturation where (m) can be calcul

The permeability is the most important parameter that indicates how efficient the reservoir fluids flow through the rock pores to the wellbore. Well-log evaluation and core measurements techniques are typically used to estimate it. In this paper, the permeability has been predicted by using classical and Flow zone indicator methods. A comparison between the two methods shows the superiority of the FZI method correlations, these correlations can be used to estimate permeability in un-cored wells with a good approximation.

Renewable energy technology is growing fast especially photovoltaic (PV) system to move the conventional electricity generation and distribution towards smart grid. However, similar to monthly electricity bill, the PV energy producers can only monitor their energy PV generation once a month. Any malfuntion in PV system components may reduce the performance of the system without notice. Thus, developing a real-time monitoring system of PV production is very crucial for early detection. In addition, electricity consumption is also important to be monitored more frequently to increase energy savings awareness among consumers. Hardware based Internet-of-Thing (IoT) monitoring and control system is widely used. However, the implementation of

Research includes three axes, the first is the average estimate time of achievement (day) to work oversight, to five supervisory departments in the Office of Financial Supervision Federal and then choose the three control outputs and at the level of each of the five departments above, and after analyzing the data statistically back to us that the distribution of the times of achievement It is the exponential distribution (Exponential Distribution) a parameter (q), and the distribution of normal (Normal Distribution) with two parameters (μ, σ²), and introduced four methods of parameter estimation (q) as well as four modalities parameter to estimate (

The reaction of [Benzoyl hydrazine] with [Diphenyl mono oxime] and Glacial acetic acid was carried out in methanol gave a new tridentate ligand [Benzoic acid (2-hydroxyimino- 1, 2-diphyneylethylidene) - hydrazide]. This ligand was reacted with some metal ions (Fe(II), Co(II), Ni(II), and Cu(II)) in methanol with (1:1) metal : ligand ratio to give a series of new complexes of the general formula [M(L)Cl2.H2O], where M= Fe(11), Co(11), Ni(11) and Cu(11). All compounds were characterized by spectroscopic methods (I.R, UV-Vis), elemental microanalysis (C.H.N), atomic absorption, magnetic susceptibility, and conductivity measurements. From the obtained data the proposed molecular structures were suggested for the complexes of Fe

The reaction of [Benzoyl hydrazine] with [Diphenyl mono oxime] and Glacial acetic acid was carried out in methanol gave a new tridentate ligand [Benzoic acid (2- hydroxyimino- 1, 2-diphyneylethylidene) - hydrazide]. This ligand was reacted with some metal ions (Fe(II), Co(II), Ni(II), and Cu(II)) in methanol with (1:1) metal : ligand ratio to give a series of new complexes of the general formula [M(L)Cl2.H2O], where M= Fe(11), Co(11), Ni(11) and Cu(11) . All compounds were characterized by spectroscopic methods (I.R, UV-Vis), elemental microanalysis (C.H.N), atomic absorption, magnetic susceptibility, and conductivity measurements. From the obtained data the proposed molecular structures were suggested for the complexes of Fe (II), Co (II)