summary of the research

The heart is the pine-shaped flesh on the left side of the chest. The moral gentleness in this flesh is called the home of perception, reason and understanding, as well as the place of desires and passions, so it turns between one desire and another between good and evil. As for its parts, it consists of four main parts called chambers, two rooms on the right As for the two chambers below, it is called the ventricle, the heart works regularly and accurately to pump blood and distribute it to all parts of the body and vital organs. And the Holy Quran divided the types of heart into two main types of healthy hearts, which are types (healthy, hidden, living....)

And the second type is sick hea

Text Clustering consists of grouping objects of similar categories. The initial centroids influence operation of the system with the potential to become trapped in local optima. The second issue pertains to the impact of a huge number of features on the determination of optimal initial centroids. The problem of dimensionality may be reduced by feature selection. Therefore, Wind Driven Optimization (WDO) was employed as Feature Selection to reduce the unimportant words from the text. In addition, the current study has integrated a novel clustering optimization technique called the WDO (Wasp Swarm Optimization) to effectively determine the most suitable initial centroids. The result showed the new meta-heuristic which is WDO was employed as t

Nowadays, a very widespread of smartphones, especially Android smartphones, is observed. This is due to presence of many companies that produce Android based phones and provide them to consumers at reasonable prices with good specifications. The actual benefit of smartphones lies in creating communication between people through the exchange of messages, photos, videos, or other types of files. Usually, this communication is through the existence of an access point through which smartphones can connect to the Internet. However, the availability of the Internet is not guaranteed in all places and at all times, such as in crowded places, remote areas, natural disasters, or interruption of the Internet connection for any reason. To create a

     In this research, we propose to use two local search methods (LSM's); Particle Swarm Optimization (PSO) and the Bees Algorithm (BA) to solve Multi-Criteria Travelling Salesman Problem (MCTSP) to obtain the best efficient solutions. The generating process of the population of the proposed LSM's may be randomly obtained or by adding some initial solutions obtained from some efficient heuristic methods. The obtained solutions of the PSO and BA are compared with the solutions of the exact methods (complete enumeration and branch and bound methods) and some heuristic methods. The results proved the efficiency of PSO and BA methods for a large number of nodes ( ). The proposed LSM's give the best efficient solutions for the MCTSP for

The current study aimed to standardize the multi-position suicidal tendency scale MAST in the Saudi environment as well as to assess suicidal tendencies in adolescents. Moreover, the study aimed to test the psychometric characteristics of the scale among a sample of (490) high school and undergraduate students, in the adolescence who ranging in age from (16-21) years. The scale demonstrated satisfactory internal consistency in terms of validity and reliability tests. as the results showed of exploratory factor analysis to the four dimensions of suicidal tendencies loading on two factors that accommodate 74.60% of the overall variance of the scale (1) the attitude toward life,  and absorbs 43, 20% of the total variance of the scale,

     The traveling salesman problem is addressed in this paper by introducing a distributed multi-ant colony algorithm that is implemented on a Raspberry Pi cluster. The implementation of a master and eight workers, each running on Raspberry Pi nodes, is the central component of this novel technique. Each worker is responsible for managing their own colony of ants, while the master coordinates communications among workers’ nodes and assesses the most optimal approach. To put the newly built cluster through its paces, several datasets of traveling salesman problem are used to test the created cluster. The findings of the experiment indicate that a single board computer cluster, which makes use of multi-ant colony algorithm, is a via

In this research is estimated the function of reliability dynamic of multi state systems  and their compounds and for three types of systems (serial, parallel, 2-out-of-3) and about two states (Failure and repair) depending on calculating the structur function allow to describing the behavior of

This paper study two stratified quantile regression models of the marginal and the conditional varieties. We estimate the quantile functions of these models by using two nonparametric methods of smoothing spline (B-spline) and kernel regression (Nadaraya-Watson). The estimates can be obtained by solve nonparametric quantile regression problem which means minimizing the quantile regression objective functions and using the approach of varying coefficient models. The main goal is discussing the comparison between the estimators of the two nonparametric methods and adopting the best one between them

Sewer systems are used to convey sewage and/or storm water to sewage treatment plants for disposal by a network of buried sewer pipes, gutters, manholes and pits. Unfortunately, the sewer pipe deteriorates with time leading to the collapsing of the pipe with traffic disruption or clogging of the pipe causing flooding and environmental pollution. Thus, the management and maintenance of the buried pipes are important tasks that require information about the changes of the current and future sewer pipes conditions. In this research, the study was carried on in Baghdad, Iraq and two deteriorations model's multinomial logistic regression and neural network deterioration model NNDM are used to predict sewers future conditions. The results of the