In this paper, the process of comparison between the tree regression model and the negative binomial regression. As these models included two types of statistical methods represented by the first type "non parameter statistic" which is the tree regression that aims to divide the data set into subgroups, and the second type is the "parameter statistic" of negative binomial regression, which is usually used when dealing with medical data, especially when dealing with large sample sizes. Comparison of these methods according to the average mean squares error (MSE) and using the simulation of the experiment and taking different sample

              Automated clinical decision support system (CDSS) acts as new paradigm in medical services today. CDSSs are utilized to increment specialists (doctors) in their perplexing decision-making. Along these lines, a reasonable decision support system is built up dependent on doctors' knowledge and data mining derivation framework so as to help with the interest the board in the medical care gracefully to control the Corona Virus Disease (COVID-19) virus pandemic and, generally, to determine the class of infection and to provide a suitable protocol treatment depending on the symptoms of patient. Firstly, it needs to determine the three early symptoms of COVID-19 pandemic criteria (fever, tiredness, dry cough and breat

           Is one of the processes of educational guidance to help the individual to design educational plans that fit with the abilities and inclinations and goals.
And research aims the current instruction program heuristic therapeutic knowledge to deal with emotional disorders. And may the researcher instruct a program according to the theories of interested and competent guidance to education and has studied the large number of studies available in this field, as has been the program on a number of specialists in education and Psychology and took their views. And then was adopted the final version of the indicative program, consistent with the sample, which was built

The current research aims to identify the level of parental treatment methods tolerance, hostility, strictness, and warmth, as well as the level of self-efficacy among middle school students. Moreover, it aims to identify the correlation relationship between the variables of parental treatment methods and self-efficacy among middle school students. The research sample included (150) middle school students. For achieving the objectives of the current research, the researchers adopted a scale of parental treatment methods prepared by (Zughair, 2006), and a scale of self-efficacy prepared by (Youssef, 2016), which were applied in their final form to the research sample. The research reached the following results: parents use a low-level hos

            In this paper the research represents an attempt of expansion in using the parametric and non-parametric estimators to estimate the median effective dose ( ED50 ) in the quintal bioassay and comparing between  these methods . We have Chosen three estimators for Comparison. The first estimator is
( Spearman-Karber )  and the second estimator is ( Moving Average ) and The Third estimator  is ( Extreme Effective Dose ) . We used a minimize Chi-square as a parametric method. We made a Comparison for these estimators by calculating the mean square error of (ED50) for each one of them and comparing it with the optimal the mean square

The proton momentum distributions (PMD) and the elastic
electron scattering form factors F(q) of the ground state for some
even mass nuclei in the 2p-1f shell for 70Ge, 72Ge, 74Ge and 76Ge are
calculated by using the Coherent Density Fluctuation Model (CDFM)
and expressed in terms of the fluctuation function (weight function)
|F(x)|2. The fluctuation function has been related to the charge
density distribution (CDD) of the nuclei and determined from the
theory and experiment. The property of the long-tail behavior at high
momentum region of the proton momentum distribution has been
obtained by both the theoretical and experimental fluctuation
functions. The calculated form factors F (q) of all nuclei under s

The zeolite's textural properties have a significant effect on zeolite's effectiveness in the different industrial processes. This research aimed to study the textual properties of the NaX and FeX zeolites using the nitrogen adsorption-desorption technique at a constant low temperature. According to the International Union of Pure and Applied Chemistry, the adsorption-desorption isotherm showed that the studied materials were mixed kinds I/II isotherms and H3 type hysteresis. The Brunauer-Emmett-Teller isotherm was the best model to describe the nitrogen adsorption-desorption better than the Langmuir and Freundlich isotherms. The obtained adsorption capacity and Brunauer-Emmett-Teller surface area values for NaX were greater than FeX. Ac

Poly (3-hydroxybutyrate) (PHB) is a typical microbial bio-polyester reserve material; known as “green plastics”, which produced under controlled conditions as intracellular products of the secondary metabolism of diverse gram-negative/positive bacteria and various extremophiles archaea. Although PHB has properties allowing being very attractive, it is too expensive to compete with conventional and non-biodegradable plastics. Feasibility of this research to evaluate the suitability of using a watermelon-derived media as an alternative substrate for PHB synthesis under stress conditions was examined. Results, include the most nutrients extraction, indicated that the watermelon seeds contain a high content of nutrients makes them a promisi

Software-defined networking (SDN) is an innovative network paradigm, offering substantial control of network operation through a network’s architecture. SDN is an ideal platform for implementing projects involving distributed applications, security solutions, and decentralized network administration in a multitenant data center environment due to its programmability. As its usage rapidly expands, network security threats are becoming more frequent, leading SDN security to be of significant concern. Machine-learning (ML) techniques for intrusion detection of DDoS attacks in SDN networks utilize standard datasets and fail to cover all classification aspects, resulting in under-coverage of attack diversity. This paper proposes a hybr