Sentiment analysis is one of the major fields in natural language processing whose main task is to extract sentiments, opinions, attitudes, and emotions from a subjective text. And for its importance in decision making and in people's trust with reviews on web sites, there are many academic researches to address sentiment analysis problems. Deep Learning (DL) is a powerful Machine Learning (ML) technique that has emerged with its ability of feature representation and differentiating data, leading to state-of-the-art prediction results. In recent years, DL has been widely used in sentiment analysis, however, there is scarce in its implementation in the Arabic language field. Most of the previous researches address other l

Background: Presence of maxillary sinus septa has been known to be a complicating factor for sinus elevation procedure and implant placement in posterior maxilla. The maxillary sinuses septa are thin walls of cortical bone inside the sinus. They vary in number, location, and height. This study aimed to discover the accuracy of Spiral Computed Tomographic Scan in evaluation the maxillary sinus septa (prevalence, location, height) in subjects with dentate, partially edentulous and completely edentulous maxilla. Material and method: This study included (267) subjects ranged from (20-70 years), (132) male and (135) female divided into three groups, (97) fully dentate group, (102) partially edentulous group and (68) completely edentulous group w

Relying on modern work strategies, such as adopting scientific inductions, consolidates the information in the learner’s memory, develops the skill work of the football player, and raises the efficiency of their motor abilities. From this standpoint, the researcher, who is a teacher at the University of Baghdad, College of Physical Education and Sports Sciences, and follows most of the sports club teams in youth football, believes that there must be From extrapolations through the machine and employing it in the field to serve the skill aspect and benefit from scientific technology in development and making it a useful tool to serve the sports field in football, as the goal of the research was the efficiency of machine extrapolation in de

Background/objectives: To study the motion equation under all perturbations effect for Low Earth Orbit (LEO) satellite. Predicting a satellite’s orbit is an important part of mission exploration. Methodology: Using 4th order Runge–Kutta’s method this equation was integrated numerically. In this study, the accurate perturbed value of orbital elements was calculated by using sub-steps number m during one revolution, also different step numbers nnn during 400 revolutions. The predication algorithm was applied and orbital elements changing were analyzed. The satellite in LEO influences by drag more than other perturbations regardless nnn through semi-major axis and eccentricity reducing. Findings and novelty/improvement: The results demo

The importance of the research is evident in the use of exercises with the training device, which is one of the modern techniques in teaching the abilities of players, especially in teaching the skill of the backhand, and in improving the accuracy of the performance of players and increasing the contribution to the formation of a base for the game for players who have a good level of learning and upgrading the game to reach a certain achievement, and the research issue was represented in the lack of accuracy in sending balls to the required areas to achieve points, especially in the performance of the skill of the backhand due to the speed of play during the course of the match, and the study aimed to introduce modern technology usi

The non static chain is always the problem of static analysis so that explained some of theoretical work, the properties of statistical regression analysis to lose when using strings in statistic and gives the slope of an imaginary relation under consideration.  chain is not static can become static by adding variable time to the multivariate analysis the factors to remove the general trend as well as variable placebo seasons to remove the effect of seasonal .convert the data to form exponential or logarithmic , in addition to using the difference repeated d is said in this case it integrated class d. Where the research contained in the theoretical side in parts in the first part the research methodology ha

The using of the parametric models and the subsequent estimation methods require the presence of many of the primary conditions to be met by those models to represent the population under study adequately, these prompting researchers to search for more flexible parametric models and these models were nonparametric, many researchers, are interested in the study of the function of permanence and its estimation methods, one of these non-parametric methods.

For work of purpose statistical inference parameters around the statistical distribution for life times which censored data , on the experimental section of this thesis has been the comparison of non-parametric methods of permanence function, the existence

Visual analytics becomes an important approach for discovering patterns in big data. As visualization struggles from high dimensionality of data, issues like concept hierarchy on each dimension add more difficulty and make visualization a prohibitive task. Data cube offers multi-perspective aggregated views of large data sets and has important applications in business and many other areas. It has high dimensionality, concept hierarchy, vast number of cells, and comes with special exploration operations such as roll-up, drill-down, slicing and dicing. All these issues make data cubes very difficult to visually explore. Most existing approaches visualize a data cube in 2D space and require preprocessing steps. In this paper, we propose a visu

This research aims to analyze and simulate biochemical real test data for uncovering the relationships among the tests, and how each of them impacts others. The data were acquired from Iraqi private biochemical laboratory. However, these data have many dimensions with a high rate of null values, and big patient numbers. Then, several experiments have been applied on these data beginning with unsupervised techniques such as hierarchical clustering, and k-means, but the results were not clear. Then the preprocessing step performed, to make the dataset analyzable by supervised techniques such as Linear Discriminant Analysis (LDA), Classification And Regression Tree (CART), Logistic Regression (LR), K-Nearest Neighbor (K-NN), Naïve Bays (NB

In recent years, data centre (DC) networks have improved their rapid exchanging abilities. Software-defined networking (SDN) is presented to alternate the impression of conventional networks by segregating the control plane from the SDN data plane. The SDN presented overcomes the limitations of traditional DC networks caused by the rapidly incrementing amounts of apps, websites, data storage needs, etc. Software-defined networking data centres (SDN-DC), based on the open-flow (OF) protocol, are used to achieve superior behaviour for executing traffic load-balancing (LB) jobs. The LB function divides the traffic-flow demands between the end devices to avoid links congestion. In short, SDN is proposed to manage more operative configur