The purpose of this study is to evaluate the effect of hydrated lime addition methods as filler replacement on fatigue performance of Hot Mix Asphalt (HMA). Three types of addition methods of hydrated lime were introduced namely dry HL on dry aggregate and saturated surface aggregate above 3% and slurry HL on dry aggregate, ordinary Lime stone powder was reduced by three HL percentage (1.0, 2.0 and 3.0 %). The effect of different methods were investigated on the fatigue properties of HMA using, third-point flexural fatigue bending Test. Pneumatic Repeated Load System (PRLS) was carried out to establish the effect of hydrated lime on the fatigue failure criteria and to select the proper hydrated lime application methods on fatigue behavior o

With the proliferation of both Internet access and data traffic, recent breaches have brought into sharp focus the need for Network Intrusion Detection Systems (NIDS) to protect networks from more complex cyberattacks. To differentiate between normal network processes and possible attacks, Intrusion Detection Systems (IDS) often employ pattern recognition and data mining techniques. Network and host system intrusions, assaults, and policy violations can be automatically detected and classified by an Intrusion Detection System (IDS). Using Python Scikit-Learn the results of this study show that Machine Learning (ML) techniques like Decision Tree (DT), Naïve Bayes (NB), and K-Nearest Neighbor (KNN) can enhance the effectiveness of an Intrusi

As the process of  estimate for model and variable selection significant is a crucial process in the semi-parametric modeling At the beginning of the modeling process often At there are many explanatory variables to Avoid the loss of any explanatory elements may be important as a result , the selection of significant variables become necessary , so the process of variable selection is not intended to simplifying  model complexity explanation , and also predicting. In this research was to use some of the semi-parametric methods (LASSO-MAVE , MAVE and The proposal method (Adaptive LASSO-MAVE) for variable selection and estimate semi-parametric single index model (SSIM) at the same time .

The purpose of this study is to compare the influence of three teaching methods, as represented by problem-based learning (PBL), the PBL with lecture method, and the conventional teaching on undergraduate physics students' group work skills among bachelor’s degree physics students. In this study, the pre- and post-test were done and the instruments were administered to the students for data collection. The actual sample size comprises of 122 students, who were selected randomly from the physics department, college of education in iraq. Overall, the statistical results rejected null hypothesis of this study. Thus, using the PBL without or with lecture method enhances the skills of the group work among the bachelor’s degree physics studen

The analysis of the classic principal components are sensitive to the outliers where they are calculated from the characteristic values and characteristic vectors of correlation matrix or variance Non-Robust, which yields an incorrect results in the case of these data contains the outliers values. In order to treat this problem, we resort to use the robust methods where there are many robust methods Will be touched to some of them.

   The robust measurement estimators include the measurement of direct robust estimators for characteristic values by using characteristic vectors without relying on robust estimators for the   variance and covariance matrices. Also the analysis of the princ

This paper shews how to estimate the parameter of generalized exponential Rayleigh (GER) distribution by three estimation methods. The first one is maximum likelihood estimator method the second one is moment employing estimation method (MEM), the third one is rank set sampling estimator method (RSSEM)The simulation technique is used for all these estimation methods to find the parameters for generalized exponential Rayleigh distribution. Finally using the mean squares error criterion to compare between these estimation methods to find which of these methods are best to the others

Background: This review aims to discuss various canine retraction techniques using frictionless mechanics. Methods: Between 1930 and February 2022, searches were conducted about various canine retraction techniques using fixed orthodontic appliances in various databases, including PubMed Central, Science Direct, Wiley Online Library, the Cochrane Library, Textbooks, Google Scholar, Research Gate, and manual searching. Results: After removing the duplicate articles, publications that described how to use archwires to perform canine retraction with the archwires were included. Conclusions: The pros and cons of various canine retraction techniques using archwires were thoroughly discussed. T-loop is the preferred spring of all because of it

Interest in the teaching profession is one of the most important steps on the road to education reform to develop the quality of education is not only through the teacher's professional competencies required, interest in the teaching profession in any society stems from fingerprints left by the teacher on his behavior and morals and their minds and their personalities. Today we are going to provide scientific, technical and research is enormous, we need more powerful skills and ways of thinking that must be acquired by the teacher. The current search is gaining importance in terms of:

1. This is the first of its kind on the researcher's knowledge _ which deals with the modern trends in t

The area of character recognition has received a considerable attention by researchers all over the world during the last three decades. However, this research explores best sets of feature extraction techniques and studies the accuracy of well-known classifiers for Arabic numeral using the Statistical styles in two methods and making comparison study between them. First method Linear Discriminant function that is yield results with accuracy as high as 90% of original grouped cases correctly classified. In the second method, we proposed algorithm, The results show the efficiency of the proposed algorithms, where it is found to achieve recognition accuracy of 92.9% and 91.4%. This is providing efficiency more than the first method.