Background: Traditional teaching methods of cardiopulmonary resuscitation (CPR) are not effective for most learners today. They may lead to lack of retention of survival skills and poor outcomes. Various methods are adopted to provide optimal, effective, and attractive teaching methods. Application (app)-based teaching can be used as an alternative way for learners to develop their knowledge and skills. Despite the large number of professional and nonprofessional trainee members, the high quality of CPR is still not fulfilled. Technology-based learning can prove to be an effective way to teach medical subjects such as pediatric cardiac resuscitation, which require an optimal teaching environ

The aim of the present work, was measuring of uranium concentrations in 25 soil samples from five locations of Al-Kut city. The samples taken from different depths ranged from soil surface to 60cm step 15 cm, for this measurement of uranium concentrations .The most widely used technique SSNTDs was chosen to be the measurement technique. Results showed that the higher concentrations were in Hai Al- Kafaat which recorded 1.49 ± 0.054 ppm . The uranium content in soil samples were less than permissible limit of UNSCEAR(11.7ppm).

Abstract

The aim of the study was to examine the level of psychological pollution among Jordanian unemployed faculty of education graduates in public and private universities. The sample of the study consisted of (413) Jordanian male and female unemployed faculty of education graduates in 2017. The researcher administrated the psychological pollution scale on the sample of the study, consisting in the final format of (37) items distributing on (4) domains. Validity and reliability for the scale were obtained. The results of the study indicated that level of psychological pollution among Jordanian unemployed faculty of education graduates in public and private universities was high (M=3.48, SD=0.83). The results

An Intelligent Internet of Things network based on an Artificial Intelligent System, can substantially control and reduce the congestion effects in the network. In this paper, an artificial intelligent system is proposed for eliminating the congestion effects in traffic load in an Intelligent Internet of Things network based on a deep learning Convolutional Recurrent Neural Network with a modified Element-wise Attention Gate. The invisible layer of the modified Element-wise Attention Gate structure has self-feedback to increase its long short-term memory. The artificial intelligent system is implemented for next step ahead traffic estimation and clustering the network. In the proposed architecture, each sensing node is adaptive and able to

The determination of river pollution impact on the performance of water treatment plants is achieved by two main objectives. The first is to study raw and treated water qualities and comparing them with standards and the second is to evaluate the treatment plants efficiency. The analyzed data were those water quality parameters in relation to physical, chemical and bacteriological characteristics for river water and produced water by seven water treatment plants located on Tigris River passing through Baghdad City.
The results of this study indicated that all raw water characteristic are within the surface water standards established by Iraqi and USA criteria except Bacterial Counts.
Tigris River water is of good quality to be trea

       The present study was performed to spotlight the potential role of soil bacteria in the Al-Rumaila oil field as a bioindicator of heavy metals pollution. For this purpose, nine soil samples were collected from different sites, with 20cm depth, to assess the pollution status depending on the total and available concentrations of heavy metals.  The result indicates pollution of the studied soils with the following metals: Cd, Cu, Fe, Zn, and Pb. The mean of total concentration for all studied metals was higher than the allowed maximum limit based on the international limit:(3.394, 3.994, 39.993, 8844.979,150.372, and 103.347 µg/g), respectively. While measuring the total Metal concentration is important in determining the de

In recent years, the number of applications utilizing mobile wireless sensor networks (WSNs) has increased, with the intent of localization for the purposes of monitoring and obtaining data from hazardous areas. Location of the event is very critical in WSN, as sensing data is almost meaningless without the location information. In this paper, two Monte Carlo based localization schemes termed MCL and MSL* are studied. MCL obtains its location through anchor nodes whereas MSL* uses both anchor nodes and normal nodes. The use of normal nodes would increase accuracy and reduce dependency on anchor nodes, but increases communication costs. For this reason, we introduce a new approach called low communication cost schemes to reduce communication

Mobile-based human emotion recognition is very challenging subject, most of the approaches suggested and built in this field utilized various contexts that can be derived from the external sensors and the smartphone, but these approaches suffer from different obstacles and challenges. The proposed system integrated human speech signal and heart rate, in one system, to leverage the accuracy of the human emotion recognition. The proposed system is designed to recognize four human emotions; angry, happy, sad and normal. In this system, the smartphone is used to   record user speech and send it to a server. The smartwatch, fixed on user wrist, is used to measure user heart rate while the user is speaking and send it, via Bluetooth,