DBN Rashid, INTERNATIONAL JOURNAL OF DEVELOPMENT IN SOCIAL SCIENCE AND HUMANITIES, 2021

The two most popular models inwell-known count regression models are Poisson and negative binomial regression models. Poisson regression is a generalized linear model form of regression analysis used to model count data and contingency tables. Poisson regression assumes the response variable Y has a Poisson distribution, and assumes the logarithm of its expected value can be modeled by a linear combination of unknown parameters. Negative binomial regression is similar to regular multiple regression except that the dependent (Y) variables an observed count that follows the negative binomial distribution. This research studies some factors affecting divorce using Poisson and negative binomial regression models. The factors are unemplo

This research is an attempt to develop exercise with weights to strengthen some of the striking muscles in the shoulder and arm and to develop the accuracy of the smash and rectum skills. The importance of this paper lies in the study of moments of force to achieve the ability to control muscular work and to explore the impact of physical and skill exercises with weights to develop moments of force for some muscles. The experimental method on a sample of players, selected according to the intentional method, including ( 9) advanced players representing Air Force Club participating in the Premier League for season 2011-2012. It is concluded that the exercises proposed have their effective impact on developing the variables of moments force f

This paper aimed to investigate the effect of the height-to-length ratio of unreinforced masonry (URM) walls when loaded by a vertical load. The finite element (FE) method was implemented for modeling and analysis of URM wall. In this paper, ABAQUS, FE software with implicit solver was used to model and analysis URM walls subjected to a vertical load. In order to ensure the validity of Detailed Micro Model (DMM) in predicting the behavior of URM walls under vertical load, the results of the proposed model are compared with experimental results. Load-displacement relationship of the proposed numerical model is found of a good agreement with that of the published experimental results. Evidence shows that load-displacement curve obtained fro

Big data of different types, such as texts and images, are rapidly generated from the internet and other applications. Dealing with this data using traditional methods is not practical since it is available in various sizes, types, and processing speed requirements. Therefore, data analytics has become an important tool because only meaningful information is analyzed and extracted, which makes it essential for big data applications to analyze and extract useful information. This paper presents several innovative methods that use data analytics techniques to improve the analysis process and data management. Furthermore, this paper discusses how the revolution of data analytics based on artificial intelligence algorithms might provide

The follower to study the markets in the Islamic Mashreq (Iraq, Persia and the country of Ma
Behind the river for the period from the reign of the Prophet Muhammad until the end of the Islamic era) to find that there
A remarkable development in the pattern, shape, planning and privatization of markets
Islamic cities and places are the main conditions for their existence, which is the mosque of the mosque
And markets, and these markets have evolved from being a space in which there are no building and no ceilings to shade them in
The places of sale and purchase to specialized markets classified according to the materials and goods produced in them
This would facilitate the task of supervising it by the market factor and

Big data analysis is essential for modern applications in areas such as healthcare, assistive technology, intelligent transportation, environment and climate monitoring. Traditional algorithms in data mining and machine learning do not scale well with data size. Mining and learning from big data need time and memory efficient techniques, albeit the cost of possible loss in accuracy. We have developed a data aggregation structure to summarize data with large number of instances and data generated from multiple data sources. Data are aggregated at multiple resolutions and resolution provides a trade-off between efficiency and accuracy. The structure is built once, updated incrementally, and serves as a common data input for multiple mining an

Owing to their remarkable characteristics, refractory molybdenum nitride (MoN x )-based compounds have been deployed in a wide range of strategic industrial applications. This review reports the electronic and structural properties that render MoN x materials as potent catalytic surfaces for numerous chemical reactions and surveys the syntheses, procedures, and catalytic applications in pertinent industries such as the petroleum industry. In particular, hydrogenation, hydrodesulfurization, and hydrodeoxygenation are essential processes in the refinement of oil segments and their conversions into commodity fuels and platform chemicals. N-vacant sites over a catalyst’s surface are a significant driver of diverse chemical phenomena. Studies