Currently, there is no established of e-waste treatment in Thi- Qar province, while their creating is increasing every year. It has been well- known that e-waste is a source of environmental degrading and their placement in landfills increases the irreversible climate change. A research model has been developed to link three components: coercive pressure, normative influence, and mimicry, then study their effect on e-waste adopt and continuance intentions. The model was validated using data collected from a field survey of 92 managers of small enterprises in Thi-Qar province.  A questionnaire was developed to collect data. It contains five major variables, exemplify by fourteen items. Als

     In this research radon concentrations in soil samples of some sites of the College of Education for Women, University of Tikrit, were measured using CR-39 nuclear impact detector. Soil samples were  prepared according to classical protocols whereby they were irradiated for a period of 65 days in propagation chambers chemically treated and subjected to optical microscopy to calculate nuclear effects. The results show differences in the concentrations of radon gas in the samples collected from different sites  ranging between a lowest value in the location of the department of English and a highest value of  in the location of the cafeteria of College compared to the radiation background of due to th

    Three monogenean species of the genus Gyrodactylus viz. G. cotti Roman, 1956 on gills of Planiliza abu, G. mikailovi Ergens & Ibragimov, 1976 on gills of Chondrostoma regium and G. prostae Ergens, 1963 on gills of Alburnus caeruleus were recorded from Tigris river at Al-Shawwaka region, Baghdad. The description and measurements of these parasites as well as their illustrations where given. All these parasites are recorded here for the first time in Iraq.  
 

During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

A series of laboratory model tests has been carried out to investigate the using of pomegranate sticks mat as reinforcement to increase the bearing capacity of footing on loose sand. The influence of depth and length of pomegranate sticks layer was examined. In the present research single layer of pomegranate sticks reinforcement was used to strengthen the loose sand stratum beneath the strip footing. The dimensions of the used foundation were 4*20 cm. The reinforcement layer has been embedded at depth 2, 4 and 8 cm under surcharge stresses . Reinforcing layer with length of 8 and 16 cm were used. The final model test results indicated that the inclusion of pomegranate sticks reinforcement is very effective in improvement the loading cap

During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

Aerial manipulation of objects has a number of advantages as it is not limited by the morphology of the terrain. One of the main problems of the aerial payload process is the lack of real-time prediction of the interaction between the gripper of the aerial robot and the payload. This paper introduces a digital twin (DT) approach based on impedance control of the aerial payload transmission process. The impedance control technique is implemented to develop the target impedance based on emerging the mass of the payload and the model of the gripper fingers. Tracking the position of the interactional point between the fingers of gripper and payload, inside the impedance control, is achieved using model predictive control (MPD) approach.

In an earlier paper, the basic analytical formula for particle-hole nuclear state densities was derived for non-Equidistant Spacing Model (non-ESM) approach. In this paper, an extension of the former equation was made to include pairing. Also a suggestion was made to derive the exact formula for the particle-hole state densities that depends exactly on Fermi energy and nuclear binding energies. The results indicated that the effects of pairing reduce the state density values, with similar dependence in the ESM system but with less strength. The results of the suggested exact formula indicated some modification from earlier non-ESM approximate treatment, on the cost of more calculation time