Back ground: One out of six children in the
world today is involved in child labor, doing
work that is damaging to his or her mental,
physical and emotional development.
Objective: Assessment of some health
problems among the studied working children.
Method; A cross-sectional study was
conducted in Al Amen Primary Health Care
(PHCC) during the period from January to
August 2009, a sample of 6048 children were
selected randomly(3218girls and2866 boys age
between 5-17 years ) and interviewed to collect
information using a structured questionnaire
form, information related to different aspects
of child labor prevention were included in the
form as well as a general medical examination
and lab

In this paper, we build a fuzzy classification system for classifying the nutritional status of children under 5 years old in Iraq using the Mamdani method based on input variables such as weight and height to determine the nutritional status of the child. Also, Classifying the nutritional status faces a difficult challenge in the medical field due to uncertainty and ambiguity in the variables and attributes that determine the categories of nutritional status for children, which are relied upon in medical diagnosis to determine the types of malnutrition problems and identify the categories or groups suffering from malnutrition to determine the risks faced by each group or category of children. Malnutrition in children is one of the most

Incorporating waste byproducts into concrete is an innovative and promising way to minimize the environmental impact of waste material while maintaining and/or improving concrete’s mechanical characteristics and strength. The proper application of sawdust as a pozzolan in the building industry remains a significant challenge. Consequently, this study conducted an experimental evaluation of sawdust as a fill material. In particular, sawdust as a fine aggregate in concrete offers a realistic structural and economical possibility for the construction of lightweight structural systems. Failure under four-point loads was investigated for six concrete-filled steel tube (CFST) specimens. The results indicated that recycled lightweight co

              Automated clinical decision support system (CDSS) acts as new paradigm in medical services today. CDSSs are utilized to increment specialists (doctors) in their perplexing decision-making. Along these lines, a reasonable decision support system is built up dependent on doctors' knowledge and data mining derivation framework so as to help with the interest the board in the medical care gracefully to control the Corona Virus Disease (COVID-19) virus pandemic and, generally, to determine the class of infection and to provide a suitable protocol treatment depending on the symptoms of patient. Firstly, it needs to determine the three early symptoms of COVID-19 pandemic criteria (fever, tiredness, dry cough and breat

Until recently, researchers have utilized and applied various techniques for intrusion detection system (IDS), including DNA encoding and clustering that are widely used for this purpose. In addition to the other two major techniques for detection are anomaly and misuse detection, where anomaly detection is done based on user behavior, while misuse detection is done based on known attacks signatures. However, both techniques have some drawbacks, such as a high false alarm rate. Therefore, hybrid IDS takes advantage of combining the strength of both techniques to overcome their limitations. In this paper, a hybrid IDS is proposed based on the DNA encoding and clustering method. The proposed DNA encoding is done based on the UNSW-NB15

Diagnosing heart disease has become a very important topic for researchers specializing in artificial intelligence, because intelligence is involved in most diseases, especially after the Corona pandemic, which forced the world to turn to intelligence. Therefore, the basic idea in this research was to shed light on the diagnosis of heart diseases by relying on deep learning of a pre-trained model (Efficient b3) under the premise of using the electrical signals of the electrocardiogram and resample the signal in order to introduce it to the neural network with only trimming processing operations because it is an electrical signal whose parameters cannot be changed. The data set (China Physiological Signal Challenge -cspsc2018) was ad

The direct electron transfer behavior of hemoglobin that is immobilized onto screen-printed carbon electrode (SPCE) modified with silver nanoparticles (AgNPs) and chitosan (CS) was studied in this work. Cyclic voltametry and spectrophotometry were used to characterize the hemoglobin (Hb) bioconjunction with AgNPs and CS. Results of the modified electrode showed quasi-reversible redox peaks with a formal potential of (-0.245 V) versus Ag/AgCl in 0.1 M phosphate buffer solution (PBS), pH7, at a scan rate of 0.1 Vs-1. The charge transfer coefficient (α) was 0.48 and the apparent electron transfer rate constant (Ks) was 0.47 s-1. The electrode was used as a hydrogen peroxide biosensor with a linear response over 3 to 240 µM and a detection li