The aim of this study was Identifying the relation of coordination and kinesthetic perception with artistic performance level in gymnastics skills for students in second class from the college of physical education/ university of Baghdad/ Al - jadreia .The searchers have been used the descriptive method in scanning style .The subject of this search has been taken (45) female - student in second class from the college of physical education/ university of Baghdad . The searchers have reached into specific conclusions concerning with statistic analysis about immoral joint relation between sensitive- kinetic coincidence and realization and with Artistic Performance Level in Gymnastics Skills for Women for second class .The an important recommen

A field experiment was carried out during two winter season 2013, 2014 at the field of the Department of Field Crops, College of Agriculture, University of Baghdad, to study the effect of seeds soaking with Gibberellic acid and foliar with Abscisic Acid on the growth, yield, and content of Anise oil seeds using factorial experiment within RCBD design with three replicates. The seeds was treated within GA3 were soaked with two concentrations of  30, and 60 mg. litter-1 in addition to without soaking and the code has been B0 , B1 , B2 overlapped these transactions with two concentrations of Abscisic Acid  3, and 6 mg. litter-1 in addition to without foliar A0 , A1 , A2The seeds to be treated  with GA3 are soaked for 24 hours prior

This paper proposes a collaborative system called Recycle Rewarding System (RRS), and focuses on the aspect of using information communication technology (ICT) as a tool to promote greening. The idea behind RRS is to encourage recycling collectors by paying them for earning points. In doing so, both the industries and individuals reap the economical benefits of such system. Finally, and more importantly, the system intends to achieve a green environment for the Earth. This paper discusses the design and implementation of the RRS, involves: the architectural design, selection of components, and implementation issues. Five modules are used to construct the system, namely: database, data entry, points collecting and recording, points reward

Assessing the accuracy of classification algorithms is paramount as it provides insights into reliability and effectiveness in solving real-world problems. Accuracy examination is essential in any remote sensing-based classification practice, given that classification maps consistently include misclassified pixels and classification misconceptions. In this study, two imaginary satellites for Duhok province, Iraq, were captured at regular intervals, and the photos were analyzed using spatial analysis tools to provide supervised classifications. Some processes were conducted to enhance the categorization, like smoothing. The classification results indicate that Duhok province is divided into four classes: vegetation cover, buildings,

In this paper, two new simple, fast and efficient block matching algorithms are introduced, both methods begins blocks matching process from the image center block and moves across the blocks toward image boundaries. With each block, its motion vector is initialized using linear prediction that depending on the motion vectors of its neighbor blocks that are already scanned and their motion vectors are assessed. Also, a hybrid mechanism is introduced, it depends on mixing the proposed two predictive mechanisms with Exhaustive Search (ES) mechanism in order to gain matching accuracy near or similar to ES but with Search Time ST less than 80% of the ES. Also, it offers more control capability to reduce the search errors. The experimental tests

With the rapid development of computers and network technologies, the security of information in the internet becomes compromise and many threats may affect the integrity of such information. Many researches are focused theirs works on providing solution to this threat. Machine learning and data mining are widely used in anomaly-detection schemes to decide whether or not a malicious activity is taking place on a network. In this paper a hierarchical classification for anomaly based intrusion detection system is proposed. Two levels of features selection and classification are used. In the first level, the global feature vector for detection the basic attacks (DoS, U2R, R2L and Probe) is selected. In the second level, four local feature vect

Nowadays, internet security is a critical concern; the One of the most difficult study issues in network security is "intrusion detection". Fight against external threats. Intrusion detection is a novel method of securing computers and data networks that are already in use. To boost the efficacy of intrusion detection systems, machine learning and deep learning are widely deployed. While work on intrusion detection systems is already underway, based on data mining and machine learning is effective, it requires to detect intrusions by training static batch classifiers regardless considering the time-varying features of a regular data stream. Real-world problems, on the other hand, rarely fit into models that have such constraints. Furthermor