Light naphtha treatment was achieved over 0.3wt%Pt loaded-alumina, HY-zeolite and Zr/W/HY-zeolite catalysts at temperature rang of 240-370°C, hydrogen to hydrocarbon mole ratio of 1-4 0.75-3 wt/wt/hr, liquid hourly space velocity (LHSV) and at atmospheric pressure. The hydroconversion of light naphtha over Pt loaded catalyst shows two main reactions; hydrocracking and hydroisomerization reactions. The catalytic conversion of a light naphtha is greatly influenced by reaction temperature, LHSV, and catalyst function. Naphtha transformation (hyroisomerization, cracking and aromatization) increases with decreasing LHSV and increasing temperature except hydroisomerization activity increases with increasing of temperature till 300°C then began

A field experiment was conducted in an agricultural field in Al-Hindia district, Karbala governorate in a silty clay soil during the year 2020. The research included a study of two factors, the first is the depth of plowing at two levels, namely 13 and 20 cm, which represented the main blocks. The second is the tire inflation pressure at two levels, namely (70 and 140 kPa), which represented the secondary blocks. Slippage percentage, field efficiency, leaf area, and 300 grain weight were studied. The experiment was carried out using a split-plot system under a Randomized complete block design, at three replications. The tillage depth of 13 cm exceeds/transcend by giving it the least slippage of (11.01%), the highest field efficiency of (50.

In this research, we use fuzzy nonparametric methods based on some smoothing techniques, were applied to real data on the Iraqi stock market especially the data about Baghdad company for soft drinks for the year (2016) for the period (1/1/2016-31/12/2016) .A sample of (148) observations was obtained in order to construct a model of the relationship between the stock prices (Low, high, modal) and the traded value by comparing the results of the criterion (G.O.F.) for three techniques , we note that the lowest value for this criterion was for the K-Nearest Neighbor at Gaussian function .

The recent advancements in security approaches have significantly increased the ability to identify and mitigate any type of threat or attack in any network infrastructure, such as a software-defined network (SDN), and protect the internet security architecture against a variety of threats or attacks. Machine learning (ML) and deep learning (DL) are among the most popular techniques for preventing distributed denial-of-service (DDoS) attacks on any kind of network. The objective of this systematic review is to identify, evaluate, and discuss new efforts on ML/DL-based DDoS attack detection strategies in SDN networks. To reach our objective, we conducted a systematic review in which we looked for publications that used ML/DL approach

     The radio drama is considered to be one of the arts that is discovered after a long period of theater's discovery. Initially , it was the broad framework of the theater's work when radio was broadcasting the shows on the huge theaters. This beginning encouraged many of the radio specialists to correlate plays with radio and make a novice and distinctive type of art. Thus, radio drama made its first step including the following   ( plays, short and long series drama as well as other types of radio arts). Because of the above mentioned , the researcher is stimulating  to study directing techniques to process the radio drama script ( Khata'a play as a sample).

The first chapter deals with the

COVID-19 is a disease that has abnormal over 170 nations worldwide. The number of infected people (either sick or dead) has been growing at a worrying ratio in virtually all the affected countries. Forecasting procedures can be instructed so helping in scheming well plans and in captivating creative conclusions. These procedures measure the conditions of the previous thus allowing well forecasts around the state to arise in the future. These predictions strength helps to make contradiction of likely pressures and significances. Forecasting procedures production a very main character in elastic precise predictions. In this case study used two models in order to diagnose optimal approach by compared the outputs. This study was introduce