Experiments were conducted to study axial liquid dispersion coefficient in slurry bubble column of 0.15 m inside diameter and 1.6 m height using perforated plate gas distributor of 54 holes of a size equal to 1 mm diameter and with a 0.24 free area of holes to the cross sectional area of the column. The three phase system consists of air, water and PVC used as the solid phase. The effect of solid loading (0, 30 and 60 kg/m³) and solid diameter (0.7, 1.5 and 3 mm) on the axial liquid dispersion coefficient at different axial location (25, 50 and 75 cm) and superficial gas velocity covered homogeneous-heterogeneous flow regime (1-10 cm/s) were studied in the present work. The results show that the axial liquid dispersion coeffic

Machine learning is considered a powerful technique in many applications such as classification, clustering, recognition and prediction. Deep learning is a modern, vital and superior machine learning that gives stunning performance, especially with huge data. Stock market price prediction is the process of determining the future value of a prospect of a financial instrument traded in the market, to gain a great profit a successful prediction must be conducted, in order to achieve that machine learning is used, in this article, two approaches are proposed to predict the stock market prices and movement using two datasets, the first approach employs two machine learning models (J48 & logistic regression) while the second approach based on rec

Lately great interests have emerged to find educational alternatives to teach and improve motor skills according to modern educational methods that take into account individual differences and speed in learning for the learner through individual learning that the learner adopts by teaching himself by passing through various educational situations to acquire skills and information in the way he is The learner is the focus of the educational process and among these alternatives the interactive video, the researchers noted through the educational training units at the Model Squash School of the Central Union, and that most of the methods and methods used in learning basic skills take a lot of time in the educational program and do not involve

This study aims to find out the effectiveness of a cognitive-behavioral counseling program in enhancing self-management in reducing the academic procrastination of tenth-grade male students. The sample consisted of (26) male students divided into an experimental group of (13) students and a control group of (13) students. Two scales of self-management and academic procrastination were used, prepared by the researcher. The counseling program was prepared by the researcher. The results showed the program's effectiveness in enhancing self-management and reducing academic procrastination in the posttest, as it showed the continuation of this enhancement in self-management and the increase in the reduction of procrastination in the follow-up

The research aims at:
1 - Detection of the degree of social values (truthfulness, honesty, cooperation) of the
primary first class students who compose members of the research sample in general.
2 - Are there significant differences at the level (0,05%) between the average degree of
members of the research sample in the values (truthfulness, honesty, cooperation) among
students enrolled and not enrolled in kindergarten and in general.
3 - Are there significant differences at the level (0,05%) between the mean scores of
individuals in the sample values (truthfulness, honesty, cooperation) in the light of two
variables: A - Gender (male / female), b - enrolled and not enrolled in kindergarten.
Having in mind that

Bioethanol production from sugar fermentation is one of the most sustainable alternatives to substitute fossil fuel. production of bioethanol from low grade dates which are rich of sugars. An available sugar from a second grade dates (reduction sugar) was 90g/l in this study. Sugar can be served as essential carbon sources for yeast growth in aerobic condition and can also be converted to bioethanol in anaerobic condition. The effect of various parameters on bioethanol production, fermentation time, pH-values, inoculum size and initial sugar concentration were varied in order to determine the optimal of bioethanol production. The highest bioethanol yield was 33g/l which was obtained with sugar concentration 90 g/l, inoculum size 1%,

Bioethanol production from sugar fermentation is one of the most sustainable alternatives to substitute fossil fuel. production of bioethanol from low grade dates which are rich of sugars. An available sugar from a second grade dates (reduction sugar) was 90g/l in this study. Sugar can be served as essential carbon sources for yeast growth in aerobic condition and can also be converted to bioethanol in anaerobic condition. The effect of various parameters on bioethanol production, fermentation time, pH-values, inoculum size and initial sugar concentration were varied in order to determine the optimal of bioethanol production. The highest bioethanol yield was 33g/l which was obtained with sugar concentration 90 g/l, inocu

Conducted two trials separate plants Defla first two seasons, 1998 and 1999 to test the susceptibility Altgveria three varieties including Azharha colored white and pink Qati and pink Qtmr and second seasons 1999 and 2000, two types color Azhaarhama white and pink Qati treated mind half-timbered two types of Alaoxinat IBA and NAA and three concentrations as well as repeatersAdhrt results low Almaah rooting

In recent years, the world witnessed a rapid growth in attacks on the internet which resulted in deficiencies in networks performances. The growth was in both quantity and versatility of the attacks. To cope with this, new detection techniques are required especially the ones that use Artificial Intelligence techniques such as machine learning based intrusion detection and prevention systems. Many machine learning models are used to deal with intrusion detection and each has its own pros and cons and this is where this paper falls in, performance analysis of different Machine Learning Models for Intrusion Detection Systems based on supervised machine learning algorithms. Using Python Scikit-Learn library KNN, Support Ve