This study is planned with the aim of constructing models that can be used to forecast trip production in the Al-Karada region in Baghdad city incorporating the socioeconomic features, through the use of various statistical approaches to the modeling of trip generation, such as artificial neural network (ANN) and multiple linear regression (MLR). The research region was split into 11 zones to accomplish the study aim. Forms were issued based on the needed sample size of 1,170. Only 1,050 forms with responses were received, giving a response rate of 89.74% for the research region. The collected data were processed using the ANN technique in MATLAB v20. The same database was utilized to develop the model of multiple linear regression (MLR) with the stepwise regression technique in the SPSS v25 software. The results indicate that the model of trip generation is related to family size and composition, gender, students’ number in the family, workers’ number in the family, and car ownership. The ANN prediction model is more accurate than the MLR predicted model: the average accuracy (AA) was 83.72% in the ANN model but only 72.46% in the MLR model.
SJ Mohammed, AA Noaimi, KE Sharquie, JM Karhoot, MS Jebur, JR Abood, A Al-Hamadani, Al-Qadisiyah Medical Journal, 2015 - Cited by 20
This research examines the quantitative analysis to assess the efficiency of the transport network in Sadr City, where the study area suffers from a large traffic movement for the variability of traffic flow and intensity at peak hours as a result of inside traffic and outside of it, especially in the neighborhoods of population with economic concentration. &n
... Show MoreThe utilization of artificial intelligence techniques has garnered significant interest in recent research due to their pivotal role in enhancing the quality of educational offerings. This study investigated the impact of employing artificial intelligence techniques on improving the quality of educational services, as perceived by students enrolled in the College of Pharmacy at the University of Baghdad. The study sample comprised 379 male and female students. A descriptive-analytical approach was used, with a questionnaire as the primary tool for data collection. The findings indicated that the application of artificial intelligence methods was highly effective, and the educational services provided to students were of exceptional quality.
... Show MoreThe utilization of artificial intelligence techniques has garnered significant interest in recent research due to their pivotal role in enhancing the quality of educational offerings. This study investigated the impact of employing artificial intelligence techniques on improving the quality of educational services, as perceived by students enrolled in the College of Pharmacy at the University of Baghdad. The study sample comprised 379 male and female students. A descriptive-analytical approach was used, with a questionnaire as the primary tool for data collection. The findings indicated that the application of artificial intelligence methods was highly effective, and the educational services provided to students were of exceptional
... Show MoreThis Study was conducted to investigate vaginitis in women who live in Baghdad City. Results Revealed that Candida spp. were the causal agent of 38.5% of symptomatic cases the yeasts Candidaalbicans, C.glabrata, C.tropicalis, C.parapsilosis and C.krusei were isolated with the percentage of 38.1, 9.1, 3.9, 2.6, 1.3 respectively also there were 18% of women in control group carrying Candida spp. The direct smear method were not efficient because the percentage of infection was 17.5% comparing with the culture method the sensitivity of direct smear method was 45.5% The percentage of WBC to Epithelial cells was less than one in 76.6% of women.
One of the bigger problems in drinking water is disinfection by-products (DBPs) that come from chlorinated disinfection. This study’s goal was to evaluate the drinking water in Al-Yarmouk Teaching Hospital, Ibn Sina Hospital and Ibn-Al-Nafis Hospital. Samples were collected between October 2018 and September 2019. Physical and chemical characteristics of the water were studied, including (temperature, hydrogen ion (pH), total dissolved solids (TDS), electrical conductivity (EC), turbidity, free residual chlorine, total organic carbon (TOC), total trihalomethanes (THMs), total halo acetic acid (THAAs)). Data analysis showed the highest value of study temperature, pH, TDS, EC, turbidity, free residual chlorine and TOC which was
... Show MoreFor cleaner air and unpolluted continue assessment study air pollution the city of
Baghdad by measuring the concentrations of air pollutants, which included TSP, Pb, where
the adoption of three stations (Andalus Square, Jadiriya, Allawi) are distributed in the city of
Baghdad in order to compare the concentrations of these pollutants with previous studies.
Study pointed out that the city's air contaminant, especially in minutes outstanding after
deducting the amount of atmospheric dust thick mechanism city this year where the highest
concentration of minutes outstanding (9895) micrograms / m 3 at the station Alawi and lower
concentration of 157 micrograms / m 3 at the station Alawi and this was higher than the
det
Dam break is series phenomenon that can result in fatal consequences and loss of properties. Unfortunately, the observed consequences can only be available after the dam breaks. Therefore, it is important to anticipate what will happen prior to dam break to issue suitable warning and locate the possible risk areas. This study attempts to simulate the case of dam break in Blue Nile at Roseires dam and see its consequences downstream. Roseires dam lies at a distance of 630 km south of Khartoum, Sennar dam lies at about 260 km downstream of Roseires dam. In this study hydraulic model is developed based of Hydraulic Engineering Centre (HEC), River Analysis System (RAS), and HEC- RAS. The HEC-RAS based model is calibrated and validated usi
... Show MoreBiometrics represent the most practical method for swiftly and reliably verifying and identifying individuals based on their unique biological traits. This study addresses the increasing demand for dependable biometric identification systems by introducing an efficient approach to automatically recognize ear patterns using Convolutional Neural Networks (CNNs). Despite the widespread adoption of facial recognition technologies, the distinct features and consistency inherent in ear patterns provide a compelling alternative for biometric applications. Employing CNNs in our research automates the identification process, enhancing accuracy and adaptability across various ear shapes and orientations. The ear, being visible and easily captured in
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