Objective: To determine the quality assurance for maternal and child health care services in Baghdad City.
Methodology: A descriptive study is conducted throughout the period of November 28th 2008 to October 10th
2009. A simple random sample of (349) is selected through the use of probability sampling approach. The study
sample was divided into four groups which include (220) consumers, (35) medical staff, (72) nursing staff and (22)
organization structure (primary health care centers). Data were collected through the use of assessment tools. It was
comprised of four questionnaires and overall items included in these questionnaires are (116) items. The study
included assessment of organization structure. Data were colle

In this study, a factorial experiment was conducted using a Randomized Complete Block Design (RCBD) with three replicates to investigate the effects of silicon at four concentrations: 0, 2, 4, and 6 ml/L, designated as S0, S1, S2, and S3, respectively and a calcium-boron combination at three concentrations: 0, (0.5 g/L Ca-EDTA, + 10 mg/L B), and (1 g/L Ca-EDTA, + 20 mg/L B), designated as C0, C1, and C2, respectively. on the activity of antioxidant enzymes and some qualitative traits of fruits. The results indicated that the studied traits were significantly influenced by the factors. Silicon application notably increased enzyme activity, treatment S3 showed the highest activity levels for peroxidase (POD) and superoxide dismutase (SOD) rea

This study includes the direct influence of (single & multi) dose of Cold Atmospheric Plasma (CAP) on the no. of platelets for mice for different exposure time (15, 30, 60, and 120) sec. the influence of CAP on mice was measured after 1, 2, 3, 7, and 14 day from exposure.
The results obtained in this study indicate that the effect of low doses of CAP on platelets was stimulatory effect in the first few hours from exposure (1day) but the high dose was inhibitory, It was found that after two weeks of exposure that the number of platelets became normal comparable to the control one, and this indicates that plasma effect was removed after this period.

CNC machines are widely used in production fields since they produce similar parts in a minimum time, at higher speed and with possibly minimum error. A control system is designed, implemented and tested to control the operation of a laboratory CNC milling machine having three axes that are moved by using a stepper motor attached to each axis. The control system includes two parts, hardware part and software part, the hardware part used a PC (works as controller) connected to the CNC machine through its parallel port by using designed interface circuit. The software part includes the algorithms needed to control the CNC. The sample needs to be machined is drawn by using one of the drawing software like AUTOCAD or 3D MAX and is saved in a we

Many academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Deci

Many academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Decision Tre

Botnet detection develops a challenging problem in numerous fields such as order, cybersecurity, law, finance, healthcare, and so on. The botnet signifies the group of co-operated Internet connected devices controlled by cyber criminals for starting co-ordinated attacks and applying various malicious events. While the botnet is seamlessly dynamic with developing counter-measures projected by both network and host-based detection techniques, the convention techniques are failed to attain sufficient safety to botnet threats. Thus, machine learning approaches are established for detecting and classifying botnets for cybersecurity. This article presents a novel dragonfly algorithm with multi-class support vector machines enabled botnet

Classifying butterfly species is crucial in biodiversity studies and environmental monitoring. However, manual classification is often a laborious process that requires specialized expertise and is prone to error, especially when species have similar visual characteristics. To address these drawbacks, this paper presents a hybrid approach that combines machine learning with deep learning for feature extraction. To enhance the visibility of important features, preprocessing techniques such as background removal and binarization are applied to butterfly images. Feature extraction was performed using the SqueezeNet convolutional neural network, pretrained on the ImageNet dataset. By discarding the final classification layer, the networ