Objectives: To evaluate health education services at primary health care centers in Kirkuk Governorate.
Methodology: A descriptive (evaluative) study a simple random sample of (384) person is selected through
the use of probability sampling approach. The sample of study is divided into three groups which include (320)
consumers, (32) health educators and (32) organization structure (in the (32) primary health care centers).
They are comprised of three questionnaires and overall items included in these questionnaires are (157) items.
The study included assessment of organization structure, such as work place, material, resources, and
workforce, demographic characteristics of care providers and consumers and activities and duties of providers.
Interviews are conducted with directors of primary health-care centers, consumers and health educators.
Results: The findings of the study indicate that there is over- load of target population on primary health care
centers, poor designed building, program statistical and data reporting system was poor, decrease core
financial support and inadequacy of funding for primary health care centers, there is increased demand and
decreased supply of primary health care health educators and Poor of strategies of training and development
for health educators and poor health education lectures for consumers in primary health-care center .
Recommendations: The study establishment of buildings for primary health care centers according to the
numbers of consumers within the geographical area. A Primary care system must grow and be nourished.
Health educators need to be expanded to meet growing community needs, once in place, must be supported
so it can continue and thrive for program reporting use to project the supply of health educators and support
of strategies of health education for consumers.
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Recurrent strokes can be devastating, often resulting in severe disability or death. However, nearly 90% of the causes of recurrent stroke are modifiable, which means recurrent strokes can be averted by controlling risk factors, which are mainly behavioral and metabolic in nature. Thus, it shows that from the previous works that recurrent stroke prediction model could help in minimizing the possibility of getting recurrent stroke. Previous works have shown promising results in predicting first-time stroke cases with machine learning approaches. However, there are limited works on recurrent stroke prediction using machine learning methods. Hence, this work is proposed to perform an empirical analysis and to investigate machine learning al
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Some degree of noise is always present in any electronic device that
transmits or receives a signal . For televisions, this signal i has been to s the
broadcast data transmitted over cable-or received at the antenna; for digital
cameras, the signal is the light which hits the camera sensor. At any case, noise
is unavoidable. In this paper, an electronic noise has been generate on
TV-satellite images by using variable resistors connected to the transmitting cable
. The contrast of edges has been determined. This method has been applied by
capturing images from TV-satellite images (Al-arabiya channel) channel with
different resistors. The results show that when increasing resistance always
produced higher noise f
Particulate matter (PM) emitted from diesel engine exhaust have been measured in terms of mass, using
99.98 % pure ethanol blended directly, without additives, with conventional diesel fuel (gas – oil),to
get 10 % , 15 %, 20 % ethanol emulsions . The resulting PM collected has been compared with those
from straight diesel. The engine used is a stationary single cylinder, variable compression ratio Ricardo
E6/US. This engine is fully instrumented and could run as a compression or spark ignition.
Observations showed that particulate matter (PM) emissions decrease with increasing oxygenate
content in the fuel, with some increase of fuel consumption, which is due to the lower heating value of
ethanol. The reduction in
The research study focuses on the efficient and accurate detection and determination of cobalt ions. The detection method involves the formation of brilliant green aggregates with calcium hexacyanoferrate in the presence of nitric acid. (Nagham-four sources of white snow light-emitting diodes arranged in three rows corresponding to three detectors) (The NAG-4SX3-3D Analyzer is an optical, chemical, electronic, and detection tool that receives a cumulative signal (no amplification is required). The total distance travelled is 760 mm with regard to YZ(mV) - tsec (dmm). It was selected for its precise calculation of the energy transducer profile. The linear range for measuring cobalt (II) ions is 0.05 to 20 mM. For concentrations of 5
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The research aims to determine the strength of the relationship between time management and work pressure and administrative leadership, where he was taken a sample of (47) of the administrative leadership at the Higher Institute of security and administrative development in the Ministry of Interior was used questionnaire as a key tool in collecting data and information and analyzed the answers to the sample surveyed by using Statistical program (spss) in the arithmetic mean of the calculation and test (t) and the correlation coefficient, the research found the most important results: the existence of significant moral positive relationship between both time management and work pressure and administrative leadership, the leadership of th
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This work is concerned with designing two types of controllers, a PID and a Fuzzy PID, to be used
for flying and stabilizing a quadcopter. The designed controllers have been tuned, tested, and
compared using two performance indices which are the Integral Square Error (ISE) and the Integral
Absolute Error (IAE), and also some response characteristics like the rise time, overshoot, settling
time, and the steady state error. To try and test the controllers, a quadcopter mathematical model has
been developed. The model concentrated on the rotational dynamics of the quadcopter, i.e. the roll,
pitch, and yaw variables. The work has been simulated with “MATLAB”. To make testing the
simulated model and the controllers m
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
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