Objective: To evaluate the client's satisfaction about the services provided in primary health care centers in the
city of Baghdad and its impact on the improvement of services.
Methodology: A simple random sample consisting of (200) clients to primary health care centers in the city of
Baghdad, (15-20) clients for each center using a questionnaire to evaluate the client's satisfaction for the service
and the use of the direct method of interview, which lasts for (6-10) minutes.
Results: Results of the study show that the number of men visits to primary health care centers, fewer women
This indicates that the most important responsibilities of family members and private health care is the
responsibility of women than

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

Activity recognition (AR) is a new interesting and challenging research area with many applications (e.g. healthcare, security, and event detection). Basically, activity recognition (e.g. identifying user’s physical activity) is more likely to be considered as a classification problem. In this paper, a combination of 7 classification methods is employed and experimented on accelerometer data collected via smartphones, and compared for best performance. The dataset is collected from 59 individuals who performed 6 different activities (i.e. walk, jog, sit, stand, upstairs, and downstairs). The total number of dataset instances is 5418 with 46 labeled features. The results show that the proposed method of ensemble boost-based classif

The definition of the role of any institution in society is achieved through its objectives, The same is true for the military and how to deal with security threats in the humanitarian field ,Terrorism, which has almost replaced the traditional pattern of war, has waged a street war and intimidated individuals, families and society ,On the other hand, he found someone to meet him from a popular crowd of volunteers to defend their homeland from different sects, sects and religions,  Thus, our study will be exposed to the role of popular mobilization in human security from a sociological point of view in Samarra, a field study of 100 male and female respondents.

The laws of the three religions tend to extend the rules and foundations of coexistence, and this is achieved in achieving the values and principles that these laws have nourished in all societies.

Our research deals with a major problem that has broken out in our societies, namely (disturbing the balance of values and behavioral standard between people), and perhaps one of the greatest causes of the problem is to move away from the correct divine discourse and sound approach, as well as corruption of common sense and the violation of its rules and found principles in the hearts of people.

        This aim research of this  discussion impact of investment in human capital dimensions (training, education, knowledge management, skills development) and its components (knowledge, skills, abilities, value) with the Office of the Inspector General's staff - Ministry of Culture in Iraq, has depended questionnaire as a tool in the collection data and information ,subjected to a measure of validity and reliability, and distributed to a sample of (63) individuals were distributed in positions (director, director of the Division of employees) have been analyzed data search using ready-statistical software (SPSS) the used hypothesis testing and correlati

Researchers are increasingly using multimodal biometrics to strengthen the security of biometric applications. In this study, a strong multimodal human identification model was developed to address the growing problem of spoofing attacks in biometric security systems. Through the use of metaheuristic optimization methods, such as the Genetic Algorithm(GA), Ant Colony Optimization(ACO), and Particle Swarm Optimization (PSO) for feature selection, this unique model incorporates three biometric modalities: face, iris, and fingerprint. Image pre-processing, feature extraction, critical image feature selection, and multibiometric recognition are the four main steps in the workflow of the system. To determine its performance, the model wa

A   new   complex  of   Cr(UI)   has   been   prepared.  The   kinetics  and eqailibrium study of  the substitution reaction   for  the complex Trans­ KfCr(ox)z(H 0)2].3l--h0 {T I }, with 4-aminoantipyrine {AAP}, bave been per£Qrm d      in  aqueous  media   at  .(pH. = 4.9,   5.6 and 6.0)   (!!?0.4M NaN03).   Activation  pararrieters   for  the  reac(ions are  {Eat= l.89l  kCal

mor 1 ,        l:t=89.29  kCal  mo1"1  &nbsp

In this work, excess properties (eg excess molar volume (VE), excess viscosity (ȠE), excess Gibbs free energy of activation of viscos flow (ΔG* E) and molar refraction changes (ΔnD) of binary solvent mixtures of tetrahydrofurfuryl alcohol (THFA) with aromatic hydrocarbons (benzene, toluene and p-xylene) have been calculated. This was achieved by determining the physical properties including density ρ, viscosity Ƞ and refraction index nD of liquid mixtures at 298.15 K. Results of the excess parameters and deviation functions for the binary solvent mixtures at 298.15 K have been discussed by molecular interactions that occur in these mixtures. Generally, parameters showed negative values and have been found to fit well to Redlich-Kister

Software-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of ne