The road transportation system is considered as major component of the infrastructure in any country, it affects the developments in economy and social activities. The Asphalt Concrete which is considered as the major pavement material for the road transportation system in Baghdad is subjected to continuous deterioration with time due to traffic loading and environmental conditions, it was felt that implementing a comprehensive pavement maintenance management system (PMMS), which should be capable for preserving the functional and structural conditions of pavement layers, is essential. This work presents the development of PMMS with Visual inspection technique for evaluating the Asphalt Concrete pavement surface condition; common types of Asphalt Concrete distress including (bleeding of Asphalt, patching, block cracking, edge cracking, longitudinal and transverse cracking, rutting, pot holes, longitudinal and transverse deformation) with their various severity and intensity conditions have been included in the system as data base. The surface of the pavement was divided into sections, and the pavement condition is visually evaluated by the raters using specially designed forms, each type of defect was measured, classified, and rated according to type, severity, and extent. Data will be fed to the system using the computer, various types of intensity and severity of distress were analyzed by the system, the present condition rating (PCR) of the pavement section is determined, and the system suggests the required maintenance action. The developed system which is assigned (PMMS-09) was verified in evaluating the pavement surface condition at AL-Jaderiah campus roadway network. The results indicated that the system is sound in evaluation of the pavement condition and in suggestion of the proper maintenance to reserve the pavement condition.
Diarrhea is one of the most commonly encountered minor ailments in the community pharmacies. It is associated with significant morbidity and mortality. However, the majority of pharmacists in Iraq did not manage diarrheal cases in a proper way. Therefore, the current study aimed to evaluate the benefit of a new mobile application (diarrhea management step by step) to improve the pharmacist's role in the management of diarrhea. The study was conducted from 21th September to 21th October 2021 using a pre-post design via a simulated patient (SP) technique. A validated diarrhea scenario was presented to each pharmacist by the SP twice, once before and the other after giving the mobile application to the pharmacist. Furthermore, pharmaci
... Show MoreThe study aimed to identify the role of public relations management in its dimensions (mental image, media, advertising, and the public) on green human resource management practices in Jordanian private hospitals in Amman, and this study relied on the quantitative approach (descriptive and analytical) to test hypotheses. Where the questionnaire was relied upon to collect data and their number was (1771) workers, and the study population consisted of workers in the hospitals that were studied on them and their number was 10 hospitals, where 316 questionnaires were distributed, 300 questionnaires were retrieved, and 16 questionnaires were not valid for analysis. That is, 91.7% of the sample, and the study relied on proportional stratified
... Show MoreIn this golden age of rapid development surgeons realized that AI could contribute to healthcare in all aspects, especially in surgery. The aim of the study will incorporate the use of Convolutional Neural Network and Constrained Local Models (CNN-CLM) which can make improvement for the assessment of Laparoscopic Cholecystectomy (LC) surgery not only bring opportunities for surgery but also bring challenges on the way forward by using the edge cutting technology. The problem with the current method of surgery is the lack of safety and specific complications and problems associated with safety in each laparoscopic cholecystectomy procedure. When CLM is utilize into CNN models, it is effective at predicting time series tasks like iden
... Show MoreA Novel artificial neural network (ANN) model was constructed for calibration of a multivariate model for simultaneously quantitative analysis of the quaternary mixture composed of carbamazepine, carvedilol, diazepam, and furosemide. An eighty-four mixing formula where prepared and analyzed spectrophotometrically. Each analyte was formulated in six samples at different concentrations thus twentyfour samples for the four analytes were tested. A neural network of 10 hidden neurons was capable to fit data 100%. The suggested model can be applied for the quantitative chemical analysis for the proposed quaternary mixture.
Among many problems that reduced the performance of the network, especially Wide Area Network, congestion is one of these, which is caused when traffic request reaches or exceeds the available capacity of a route, resulting in blocking and less throughput per unit time. Congestion management attributes try to manage such cases. The work presented in this paper deals with an important issue that is the Quality of Service (QoS) techniques. QoS is the combination effect on service level, which locates the user's degree of contentment of the service. In this paper, packet schedulers (FIFO, WFQ, CQ and PQ) were implemented and evaluated under different applications with different priorities. The results show that WFQ scheduler gives acceptable r
... Show MoreThis study uses an Artificial Neural Network (ANN) to examine the constitutive relationships of the Glass Fiber Reinforced Polymer (GFRP) residual tensile strength at elevated temperatures. The objective is to develop an effective model and establish fire performance criteria for concrete structures in fire scenarios. Multilayer networks that employ reactive error distribution approaches can determine the residual tensile strength of GFRP using six input parameters, in contrast to previous mathematical models that utilized one or two inputs while disregarding the others. Multilayered networks employing reactive error distribution technology assign weights to each variable influencing the residual tensile strength of GFRP. Temperatur
... Show MoreA Novel artificial neural network (ANN) model was constructed for calibration of a multivariate model for simultaneously quantitative analysis of the quaternary mixture composed of carbamazepine, carvedilol, diazepam, and furosemide. An eighty-four mixing formula where prepared and analyzed spectrophotometrically. Each analyte was formulated in six samples at different concentrations thus twenty four samples for the four analytes were tested. A neural network of 10 hidden neurons was capable to fit data 100%. The suggested model can be applied for the quantitative chemical analysis for the proposed quaternary mixture.
In the literature, several correlations have been proposed for bubble size prediction in bubble columns. However these correlations fail to predict bubble diameter over a wide range of conditions. Based on a data bank of around 230 measurements collected from the open literature, a correlation for bubble sizes in the homogenous region in bubble columns was derived using Artificial Neural Network (ANN) modeling. The bubble diameter was found to be a function of six parameters: gas velocity, column diameter, diameter of orifice, liquid density, liquid viscosity and liquid surface tension. Statistical analysis showed that the proposed correlation has an Average Absolute Relative Error (AARE) of 7.3 % and correlation coefficient of 92.2%. A
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