This research is an attempt to develop exercise with weights to strengthen some of the striking muscles in the shoulder and arm and to develop the accuracy of the smash and rectum skills. The importance of this paper lies in the study of moments of force to achieve the ability to control muscular work and to explore the impact of physical and skill exercises with weights to develop moments of force for some muscles. The experimental method on a sample of players, selected according to the intentional method, including ( 9) advanced players representing Air Force Club participating in the Premier League for season 2011-2012. It is concluded that the exercises proposed have their effective impact on developing the variables of moments force f

The problem of this research lies in the fact that there is a lack of accurate scientific perceptions about the size of the use of Iraqi women’s social networking sites and the motives behind this use and the expectations generated by them.
The goals of the research are as follows:
1- Determine the extent of Iraqi women’s use of social networking sites (Facebook, YouTube, twitter, and Instagram).
2- Investigative the motives behind the use of social networking sites by Iraqi women.
3- Detecting the repercussions of Iraqi women’s use of social networking sites (Facebook, you tube, twitter, and Instagram).
The research is classified as a descriptive one. The researchers use the survey methodology. The research commu

Semantic segmentation is an exciting research topic in medical image analysis because it aims to detect objects in medical images. In recent years, approaches based on deep learning have shown a more reliable performance than traditional approaches in medical image segmentation. The U-Net network is one of the most successful end-to-end convolutional neural networks (CNNs) presented for medical image segmentation. This paper proposes a multiscale Residual Dilated convolution neural network (MSRD-UNet) based on U-Net. MSRD-UNet replaced the traditional convolution block with a novel deeper block that fuses multi-layer features using dilated and residual convolution. In addition, the squeeze and execution attention mechanism (SE) and the s

The field of autonomous robotic systems has advanced tremendously in the last few years, allowing them to perform complicated tasks in various contexts. One of the most important and useful applications of guide robots is the support of the blind. The successful implementation of this study requires a more accurate and powerful self-localization system for guide robots in indoor environments. This paper proposes a self-localization system for guide robots.  To successfully implement this study, images were collected from the perspective of a robot inside a room, and a deep learning system such as a convolutional neural network (CNN) was used. An image-based self-localization guide robot image-classification system delivers a more accura

Nowadays, university education stands in front of both students who feel they are weak and teachers who are addicted to using traditional and dependent teaching. This has led to have negative repercussions on the learner from different aspects, including the mental aspect and the academic achievement process. Therefore, the present research is concerned with finding a new teaching method that adopts the motivation by the fear of failure technique. Thus, the study aims to examine the effect of adopting this method on students’ academic achievement. To achieve this aim, an experimental method was used, and an achievement test was built for the curriculum material of level two students. The pretest test was applied on 17 male and female s

Two simple methods for the determination of eugenol were developed. The first depends on the oxidative coupling of eugenol with p-amino-N,N-dimethylaniline (PADA) in the presence of K3[Fe(CN)6]. A linear regression calibration plot for eugenol was constructed at 600 nm, within a concentration range of 0.25-2.50 μg.mL–1 and a correlation coefficient (r) value of 0.9988. The limits of detection (LOD) and quantitation (LOQ) were 0.086 and 0.284 μg.mL–1, respectively. The second method is based on the dispersive liquid-liquid microextraction of the derivatized oxidative coupling product of eugenol with PADA. Under the optimized extraction procedure, the extracted colored product was determined spectrophotometrically at 618 nm. A l

Adverse drug reactions (ADR) are important information for verifying the view of the patient on a particular drug. Regular user comments and reviews have been considered during the data collection process to extract ADR mentions, when the user reported a side effect after taking a specific medication. In the literature, most researchers focused on machine learning techniques to detect ADR. These methods train the classification model using annotated medical review data. Yet, there are still many challenging issues that face ADR extraction, especially the accuracy of detection. The main aim of this study is to propose LSA with ANN classifiers for ADR detection. The findings show the effectiveness of utilizing LSA with ANN in extracting AD

The title compound, [Ru(C12H7Br2N2)2(CO)2], possesses a distorted octahedral environment about the Ru atom, with two cyclometallated 4,40-dibromoazobenzene ligands and two mutually cis carbonyl ligands. The donor atoms are arranged such that the N atoms are respectively trans to a carbonyl ligand and an aryl C atom. Comment The title compound, (I), has been prepared as a minor product of the reaction of Ru3(CO)12 and 4,40-dibromoazobenzene in refluxing n-octane; the major product is the cluster complex Ru3(3-NC6H4Br)2(CO)9 (Willis et al., 2005). Two strong (CO) absorptions at 2039 and 1991 cm1 in the IR spectrum of (I) are consistent with the presence of two mutually cis carbonyl groups. The crystal structure was investigated to ascertai