The prevalence of using the applications for the internet of things (IoT) in many human life fields such as economy, social life, and healthcare made IoT devices targets for many cyber-attacks. Besides, the resource limitation of IoT devices such as tiny battery power, small storage capacity, and low calculation speed made its security a big challenge for the researchers. Therefore, in this study, a new technique is proposed called intrusion detection system based on spike neural network and decision tree (IDS-SNNDT). In this method, the DT is used to select the optimal samples that will be hired as input to the SNN, while SNN utilized the non-leaky integrate neurons fire (NLIF) model in order to reduce latency and minimize devices

The Early – Middle Miocene Ghar and Lower Fars sedimentary succession at the representative oil-well Nu-18 of the Nahr Umr oil field south Iraq; is taken by this study to investigate the sedimentological to reservoir rock facies buildups and related reservoir zonation; as first rock-typing attempt for the both formations. The sedimentological characterization of the Early Miocene Ghar formation is mainly comprised by successive buildups of sands-gravels and sandstones, whereas; the Middle Miocene Lower Fars formation is started by limestone, limestone-marly/marl anhydritic, upgraded into interbedded-series of marl and anhydrite facies, with less-common occurrences of thin-sandstone interlayers, terminated by marl-sandy-secti

Diabetes is one of the increasing chronic diseases, affecting millions of people around the earth. Diabetes diagnosis, its prediction, proper cure, and management are compulsory. Machine learning-based prediction techniques for diabetes data analysis can help in the early detection and prediction of the disease and its consequences such as hypo/hyperglycemia. In this paper, we explored the diabetes dataset collected from the medical records of one thousand Iraqi patients. We applied three classifiers, the multilayer perceptron, the KNN and the Random Forest. We involved two experiments: the first experiment used all 12 features of the dataset. The Random Forest outperforms others with 98.8% accuracy. The second experiment used only five att

Objective: to assess the risk factors of coronary artery disease patients.
Methodology: A non-probability (purposive) sample of (100) patients. The study population consisted of
a sample of adults from both genders whose ages were 30 years and more, and was newly diagnosed as
having CAD by coronary angiography in the cardiac catheterization unit of An Nasiriyah heart center.
Results: The result of the study showed that the most common modifiable risk factors were low HDL-C
levels (58%), smoking (53%), hypertension (46%), diabetes mellitus (34%), obesity (30%), high
triglycerides (19%), hypercholesterolemia (17%), and high LDLC (14%). All these factors were positively
and significantly associated with the development

study was conducted on a stretch of Tigris river crossing Baghdad city to determine the concentration of some chlorophenols pollutants. Aqueous samples were preliminary enriched about 500 times and the chlorophenols have determined using high performance liquid chromatography HPLC. Limits of detection LOD were (0.007–0.012 mg L-1), relative standard deviations RSD% were 2.4%–5.59% and relative recoveries were 51.06%– 104.07%. The existence of chlorophenols in Tigris river was in the range 0.023–4.596 mg L-1. The developed method suggested in this study can be applied for routine analysis and monitoring of chlorinated phenols in environmental aqueous samples.

Aerial Robot Arms (ARAs) enable aerial drones to interact and influence objects in various environments. Traditional ARA controllers need the availability of a high-precision model to avoid high control chattering. Furthermore, in practical applications of aerial object manipulation, the payloads that ARAs can handle vary, depending on the nature of the task. The high uncertainties due to modeling errors and an unknown payload are inversely proportional to the stability of ARAs. To address the issue of stability, a new adaptive robust controller, based on the Radial Basis Function (RBF) neural network, is proposed. A three-tier approach is also followed. Firstly, a detailed new model for the ARA is derived using the Lagrange–d’A

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

The role of filamentous bacteria represented by Streptomycessp was studied as biological treatment for activated sludge AL- Restomia treatment unit in Baghdad city. The result shows reducing in phosphate concentration where apprise in started entrance the treatment unit 12.083 mg/L fast the unit stages reached to 8.426 mg /L where nitrate concentration apprises 3.59 mg/l and ending in 2.43 mg/L The concentration of ammonia apprises 1358 mg/L and reached to 140 mg/L. also the TDS concentration reduced from 1426 to 1203 mg/L where nutrient which represented (SO4, Mg, Ca, Na, K) reduced by range 30.883- 23.337 , 194- 121 , 440- 321 , 109.03- 101.53 and 16.85- 15.4mg/L respectively COD reduce from427.263- 82mg/L with absorbance0.018- 0.027

This study was conducted to determine the ability of water treatment system (Vortisand) to reduce some chemical and physical properties for tigris river raw water, It consisted of turbidity, electrical conductivity, pH, total hardness, calcium Hardness as well as temperature in order to determine the unit`s efficiency for reducing their concentration as compared to those in the water produced by some classical potable water projects (Dora and Wathba) in Baghdad. Samples were collected during the cold months (December 2016 and January 2017) and during the hot months (May and June 2017). The results showed that this system has the ability to reduce some properties such as turbidity, the values were 215NTU in raw water and decreased to NTU

This research consists of two parts, the first part concern with analyzing the collected data of BOD and COD values in discharge waste water from Al-Dora refinery during 2010 to find the relationship between these two variables The results indicates that there is a high correlation between BOD and COD when using a natural logarithm model (0.86 ln(COD)) with correlation coefficient of 0.98. This relationship is useful in predicting the BOD value using the COD value. The second part includes analyzing collected data from the same site in order to find a relationsip between BOD and other parameters COD, Phenol(phe), Temperature(T), Oil, Sulphat(SO4),pH and Total dissolved solids( TDS) discharged from the refinery. The results indicated that th