This paper includes an experimental study of hydrogen mass flow rate and inlet hydrogen pressure effect on the fuel cell performance. Depending on the experimental results, a model of fuel cell based on artificial neural networks is proposed. A back propagation learning rule with the log-sigmoid activation function is adopted to construct neural networks model. Experimental data resulting from 36 fuel cell tests are used as a learning data. The hydrogen mass flow rate, applied load and inlet hydrogen pressure are inputs to fuel cell model, while the current and voltage are outputs. Proposed model could successfully predict the fuel cell performance in good agreement with actual data. This work is extended to developed fuel cell feedback

KE Sharquie, AA Noaimi, MS Al-Zoubaidi, Journal of Cosmetics, Dermatological Sciences and Applications, 2015 - Cited by 8

Some maps of the chaotic firefly algorithm were selected to select variables for data on blood diseases and blood vessels obtained from Nasiriyah General Hospital where the data were tested and tracking the distribution of Gamma and it was concluded that a Chebyshevmap method is more efficient than a Sinusoidal map method through mean square error criterion.

Gestational diabetes mellitus (GDM) is a complication of gestation that is characterized by impaired glucose tolerance with first recognition during gestation. It develops when ?- cell of pancreas fail to compensate the diminished insulin sensitivity during gestation. This study aims to investigate the relationship between mother adiponectin level and ?- cell dysfunction with development gestational diabetes mellitus (GDM) and other parameters in the last trimester of pregnancy. This study includes (80) subjects ( pregnant women) in the third trimester of pregnancy, (40) healthy pregnant individuals as control group aged between (17 - 42) years and (40) gestational diabetes mellitus patients with aged between (20 - 42) years. The f

BACKGROUND: Sickle cell nephropathy, a heterogeneous group of renal abnormalities resulting from complex interactions of sickle cell disease (SCD)-related factors and non-SCD phenotype characteristics, is associated with an increased risk for morbidity and mortality. AIMS: The aims of this study were to determine the frequency of microalbuminuria (MA) among pediatric patients with SCD and to determine risk factors for MA among those patients. SUBJECTS AND METHODS: A case–control study was carried out on 120 patients with SCD, 2–18 years old, registered at Basrah Center for Hereditary Blood Diseases, and 132 age-and sex-matched healthy children were included as a control group. Investigations included complete blood panel, blood urea, se

Background: There are various secreted proteins affecting the prognosis of oral squamous cell carcinoma (OSCC) and one of them is Angiopoietin-2(Ang-2) which is thought to have an essential role in the development and progression of the tumor. Aim of the study: This study was conducted to determine the expression of (Ang-2) in (OSCC) to assess its correlations with clinicopathological parameters of the tumor. Material and Methods: 36 formalin- fixed, paraffin- embedded tissue blocks histologically diagnosed as OSCC were examined for Ang-2 immunohistochemical expression semi quantitively. Results: The expression of Ang-2 was significantly associated with histopathological grade (P value=0.023), while there is no significant association wi