Longitudinal data is becoming increasingly common, especially in the medical and economic fields, and various methods have been analyzed and developed to analyze this type of data.

In this research, the focus was on compiling and analyzing this data, as cluster analysis plays an important role in identifying and grouping co-expressed subfiles over time and employing them on the nonparametric smoothing cubic B-spline model, which is characterized by providing continuous first and second derivatives, resulting in a smoother curve with fewer abrupt changes in slope. It is also more flexible and can pick up on more complex patterns and fluctuations in the data.

The longitudinal balanced data profile was compiled into subgroup

Potential data interpretation is significant for subsurface structure characterization. The current study is an attempt to explore the magnetic low lying between Najaf and Diwaniyah Cities, In central Iraq. It aims to understand the subsurface structures that may result from this anomaly and submit a better subsurface structural image of the region. The study area is situated in the transition zone, known as the Abu Jir Fault Zone. This tectonic boundary is an inherited basement weak zone extending towards the NW-SE direction. Gravity and magnetic data processing and enhancement techniques; Total Horizontal Gradient, Tilt Angle, Fast Sigmoid Edge Detection, Improved Logistic, and Theta Map filters highlight source boundaries and the

The Fylex extract exert a high inhibition effect against A . flavus growth on PDA medium, as the fungus growth was completely inhibited by 100% at a concentration of 0.2 and 0.3% of studied extract, while the lowest inhibition percentage (71%) was found at a concentration of 0.1%. Whereas magnesium oxide nanoparticles showed the highest inhibition ratio of A. flavus (100%) was detected at 0.2% and the lowest inhibition ratio (81.66%) was at concentration 0.5%. Moreover, the addition of G. lucidum powder to PDA medium with a concentration of 2.5 mg increased the inhibition rate of A. flavus growth which was 54.4%, while the lowest inhibition ration (18.22%) was found at a concentration of 1000 mg. The milky liquid (brocade milk) of Calotropi

Abstract

This study aims to identify the most prominent factors that lead to bullying of students with intellectual disabilities in primary and middle schools from the perspectives of special education teachers. A quantitative descriptive approach was utilized. A questionnaire was used as a tool for data collection. The sample consisted of (72) male and female teachers from the Asir region in the Kingdom of Saudi Arabia. The results revealed the most prominent factors that lead to bullying as follows: factors associated with the school and its policies, factors associated with peers, factors associated with students with intellectual disabilities, and factors associated with general education teachers. The findin

This research aims to identify the factors effecting the investigation of insurance fraud from the perspective of the National Insurance Company employees, by analyzing the study variables and make recommendations on how to enhance the company and employees performance, and to achieve the objectives of the study and test hypotheses a questionnaire was designed after referring to the international standards  and the 1969 Iraqi punishment law, and it was answered by 20 employees that were approved for the purposes of  this research and analysis.

      The study found that lack of employee training was a strong factor, while the supervisory staff and operational procedures was a weak one.

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The Estimation Of The Reliability Function Depends On The Accuracy Of The Data Used To Estimate The Parameters Of The Probability distribution, and Because Some Data Suffer from a Skew in their Data to Estimate the Parameters and Calculate the Reliability Function in light of the Presence of Some Skew in the Data, there must be a Distribution that has flexibility in dealing with that Data. As in the data of Diyala Company for Electrical Industries, as it was observed that there was a positive twisting in the data collected from the Power and Machinery Department, which required distribution that deals with those data and searches for methods that accommodate this problem and lead to accurate estimates of the reliability function,

Anomaly detection is still a difficult task. To address this problem, we propose to strengthen DBSCAN algorithm for the data by converting all data to the graph concept frame (CFG). As is well known that the work DBSCAN method used to compile the data set belong to the same species in a while it will be considered in the external behavior of the cluster as a noise or anomalies. It can detect anomalies by DBSCAN algorithm can detect abnormal points that are far from certain set threshold (extremism). However, the abnormalities are not those cases, abnormal and unusual or far from a specific group, There is a type of data that is do not happen repeatedly, but are considered abnormal for the group of known. The analysis showed DBSCAN using the

The Machine learning methods, which are one of the most important branches of promising artificial intelligence, have great importance in all sciences such as engineering, medical, and also recently involved widely in statistical sciences and its various branches, including analysis of survival, as it can be considered a new branch used to estimate the survival and was parallel with parametric, nonparametric and semi-parametric methods that are widely used to estimate survival in statistical research. In this paper, the estimate of survival based on medical images of patients with breast cancer who receive their treatment in Iraqi hospitals was discussed. Three algorithms for feature extraction were explained: The first principal compone