In this study, multi-objective optimization of nanofluid aluminum oxide in a mixture of water and ethylene glycol (40:60) is studied. In order to reduce viscosity and increase thermal conductivity of nanofluids, NSGA-II algorithm is used to alter the temperature and volume fraction of nanoparticles. Neural network modeling of experimental data is used to obtain the values of viscosity and thermal conductivity on temperature and volume fraction of nanoparticles. In order to evaluate the optimization objective functions, neural network optimization is connected to NSGA-II algorithm and at any time assessment of the fitness function, the neural network model is called. Finally, Pareto Front and the corresponding optimum points are provided and

Research Summary

In this paper all possible regressions procedure as well as stepwise regression procedure were applied to select the best regression equation that explain the effect of human capital represented by different levels of human cadres on the productivity of the processing industries sector in Iraq by employing the data of a time series consisting of 21 years period. The statistical program SPSS was used to perform the required calculations.

Objective)s): To evaluate the quality of life for adult clients with hypermobility syndrome at private clinics in Baghdad City. Methodology: A cross-sectional study used a purposive ‘’non-probability’’ sample of (75) adult clients with Hypermobility Syndrome (HMS) male and female who age (25-64) years. The data were collected through the utilization of standard developed questionnaire of the world health organization (WHO). Data collected by interview with each client who is involved in the study. Each interview takes approximately (20) minutes. Results: The study revealed that there is an effect of hypermobility syndrome on the quality of life, which recorded fair level in general. The study also reported that there is an effect

دُرِست العوامل المؤثرة في عدد ساعات تجهيز الكهرباء في مدينة بغداد، وتكونت عينة الدراسة من (365) مشاهدة يومية لعام 2018، وتمثلت بستة متغيرات استعملت في الدراسة. كان الهدف الرئيس هو دراسة العلاقة بين هذه المتغيرات، وتقدير تأثيرات المتغيرات التنبؤية في المتغير التابع (عدد ساعات تجهيز الكهرباء في مدينة بغداد). ولتحقيق ذلك استعملت نمذجة المعادلات الهيكلية/ تحليل المسار وبرنامج AMOS

Problem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a

Until today, one of the leading predominant infections is Urinary tract infection (UTI). It exerts a huge burden on health systems worldwide each year. Treating UTIs empirically with antimicrobials improves morbidity rates. This study aims to assess the prevalence of UTI-associated bacteria in adult patients and to determine their antibiotic susceptibility profile. A retrospective study was conducted for adult outpatients who visited Al-Diwaniya tertiary hospitals from January 2020 till February 2022 to review their medical and lab records in addition to sociodemographic data. A total of 256 patients’ records were included of which 204 (79.7%) belong to females and 52 (20.3%) were males with an average age of 39.22±17.10 years. T

Until today, one of the leading predominant infections is Urinary tract infection (UTI). It exerts a huge burden on health systems worldwide each year. Treating UTIs empirically with antimicrobials improves morbidity rates. This study aims to assess the prevalence of UTI-associated bacteria in adult patients and to determine their antibiotic susceptibility profile. A retrospective study was conducted for adult outpatients who visited Al-Diwaniya tertiary hospitals from January 2020 till February 2022 to review their medical and lab records in addition to sociodemographic data. A total of 256 patients’ records were included of which 204 (79.7%) belong to females and 52 (20.3%) were males with an average age of 39.22±17.10 years. The pr