A new concrete rheometer is introduced including its innovation, actual design, working rules,
calibration, and reliability. A modified design of Tattersall two-point device is created. Some of
components are purchased from local and foreign markets, while other components and the
manufacturing process are locally fabricated. The matching viscosity method of determining the mixer
viscometer constants is demonstrated and followed to relate torque and rotational speed to yield stress
and viscosity (Bingham parameters). The calibration procedures and its calculation are explained.
Water is used as a Newtonian fluid, while; cement paste (cement + water) with w/c ratio equal to
(0.442) is used as a non-Newtonian fluid. Th

Imagination as a Path to Reality

Migration today is a global problem and is an extraordinary social phenomenon that affects countries around the world. Globalization, demographic shifts, political persecution, wars, armed conflicts, natural and environmental disasters, lack of skills, employment and other reasons in many countries have accelerated global migration rates. It has been observed in recent years that there is a rapid feminization of all forms and stages of migration. Women now make up nearly half of the migrant population around the world, and it appears that women have their own motives for migration in addition to family reunification in escaping Gender discrimination, political violence, and social independence, economic motives and the desire for better opp

In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction acc

Praise be to God, Lord of the worlds, and the best of prayers, and extradition was made to our master Muhammad and his whole family and companions:
And after:
Surat Al-Qariah is from the royal fence, which is in the thirtieth part of the Noble Qur’an. The commentators differed on the number of verses, and the reason for its naming. This surah talked about the conditions of people on the Day of Resurrection, and about how people were removed from their graves, all of which I spoke about in the preamble.
The research is divided into six topics: the first topic dealt with strange terms, while the second topic dealt with the most important audio issues mentioned in the surah, namely (slurring, advertising, substitution, and silenc

This study had succeeded in producing a new graphical representation of James abacus called nested chain abacus. Nested chain abacus provides a unique mathematical expression to encode each tile (image) using a partition theory where each form or shape of tile will be associated with exactly one partition.Furthermore, an algorithm of nested chain abacus movement will be constructed, which can be applied in tiling theory.

Discriminant between groups is one of the common procedures because of its ability to analyze many practical phenomena, and there are several methods can be used for this purpose, such as linear and quadratic discriminant functions. recently, neural networks is used as a tool to distinguish between groups.

In this paper the simulation is used to compare neural networks and classical method for classify observations to group that is belong to, in case of some variables that don’t follow the normal distribution. we use the proportion of number of misclassification observations to the all observations as a criterion of comparison.  

. In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction a