Abstract:

Objective(s): The present study aims to evaluate the effectiveness of Health educational program on nurses' knowledge toward children pneumonia at Al-Amara City hospitals..

Methods: A quasi –experimental study design two-study group (pretest-posttest 1 and posttest 2) carried out at Alzahrawy Hospital and Child and maternity hospital in Al Amara City to identify the effectiveness of the Health educational program on Nurses Knowledge toward Children pneumonia; the study was conducted between 1 of September 2019 to 1 of April 2020. A Purposive (Non-probability) sample is chosen for the present study. The size of sample is (60) nur

Objective(s): The present study aims to evaluate the effectiveness of Health educational program on nurses' knowledge toward children pneumonia at Al-Amara City hospitals..

 Methodology: A quasi –experimental study design two-study group (pretest-posttest 1 and posttest 2) carried out at Alzahrawy Hospital and Child and maternity hospital in Al Amara City to identify the effectiveness of the Health educational program on Nurses Knowledge toward Children pneumonia; the study was conducted between 1 of September 2019 to 1 of April 2020. A Purposive (Non-probability) sample is chosen for the present study. The size of sample is (60) nurses divided into two gr

This study aims to model the flank wear prediction equation in metal cutting, depending on the workpiece material properties and almost cutting conditions. A new method of energy transferred solution between the cutting tool and workpiece was introduced through the flow stress of chip formation by using the Johnson-Cook model. To investigate this model, an orthogonal cutting test coupled with finite element analysis was carried out to solve this model and finding a wear coefficient of cutting 6061-T6 aluminum and the given carbide tool.

An application of neural network technique was introduced in modeling the point efficiency of sieve tray, based on a
data bank of around 33l data points collected from the open literature.Two models proposed,using back-propagation
algorithm, the first model network consists: volumetric liquid flow rate (QL), F foctor for gas (FS), liquid density (pL),
gas density (pg), liquid viscosity (pL), gas viscosity (pg), hole diameter (dH), weir height (hw), pressure (P) and surface
tension between liquid phase and gas phase (o). In the second network, there are six parameters as dimensionless
group: Flowfactor (F), Reynolds number for liquid (ReL), Reynolds number for gas through hole (Reg), ratio of weir
height to hole diqmeter

The shear strength of soil is one of the most important soil properties that should be identified before any foundation design. The presence of gypseous soil exacerbates foundation problems. In this research, an approach to forecasting shear strength parameters of gypseous soils based on basic soil properties was created using Artificial Neural Networks. Two models were built to forecast the cohesion and the angle of internal friction. Nine basic soil properties were used as inputs to both models for they were considered to have the most significant impact on soil shear strength, namely: depth, gypsum content, passing sieve no.200, liquid limit, plastic limit, plasticity index, water content, dry unit weight, and initial

Breast cancer is a heterogeneous disease characterized by molecular complexity. This research utilized three genetic expression profiles—gene expression, deoxyribonucleic acid (DNA) methylation, and micro ribonucleic acid (miRNA) expression—to deepen the understanding of breast cancer biology and contribute to the development of a reliable survival rate prediction model. During the preprocessing phase, principal component analysis (PCA) was applied to reduce the dimensionality of each dataset before computing consensus features across the three omics datasets. By integrating these datasets with the consensus features, the model's ability to uncover deep connections within the data was significantly improved. The proposed multimodal deep

    The research addressed the ecological impact of the industrial product as one of the basic aesthetic elements in urban design. The research discussed the nature of the overall ecosystems of the industrial product in urban spaces, and the type of impact they have on each other. The discussion of impacts started from the identification of cognitive and non-cognitive viewpoints in the vision of ecological aesthetics, passing through the inputs of cognitive systems that see that the ecosystem made of the urban space with the existence of the industrial product as one of its constituents, are in fact systems  based on functional symmetry   between urban space design and the  design of the industrial prod

Background: This study aimed to use the combined mesio-distal crowns widths of maxillary incisors and first molars as predictors to the combined mesio-distal crowns widths of maxillary and mandibular canines and premolars. Materials and methods: The sample included 110 Iraqi Arab subjects with an age ranged between 17-25 years and class I skeletal and dental relations. The crown widths of maxillary teeth and mandibular canines and premolars were measured at the largest mesio-distal dimension on the study casts using digital electronic caliper with 0.01 mm sensitivity. Pearson’s correlation coefficient was used to determine the relation between the combined mesio-distal crowns widths of maxillary incisors and first molars and the combined

High vehicular mobility causes frequent changes in the density of vehicles, discontinuity in inter-vehicle communication, and constraints for routing protocols in vehicular ad hoc networks (VANETs). The routing must avoid forwarding packets through segments with low network density and high scale of network disconnections that may result in packet loss, delays, and increased communication overhead in route recovery. Therefore, both traffic and segment status must be considered. This paper presents real-time intersection-based segment aware routing (RTISAR), an intersection-based segment aware algorithm for geographic routing in VANETs. This routing algorithm provides an optimal route for forwarding the data packets toward their destination