Technological development intersects with terrorism to a large extent, beyond the use of the Internet and social media, in order to spread ideas, obtain support and financing, and recruit new elements, to the area of tactics and techniques of terrorist attacks, and everything related to the arsenal of terrorist weapons in the present and future, while technology offers many benefits. In various fields, and contribute to achieving multiple gains for humanity, they provide extremist and terrorist organizations and elements with a set of weapons and means through which they attempt to bypass monitoring and control efforts and the restrictions imposed on the use of weapons. They also help in planning and implementing their terrorist operations, after the terrorist was part of the weapon. Used in the terrorist operation, other types of weapons, tools and means have entered the terrorist scene. The weapons used have allowed the implementation of operations across distances, through remote control devices, drones and other technologies that enable terrorist elements to amplify the effect of operations according to In order to reduce costs, including the costs of terrorist elements carrying out operations, and causing the greatest amount of losses and terror in the targeted community or the country.
This investigation aimed to explain the mechanism of MFCA by applying this method on air-cooled engine factory which was suffering from high production cost. The results of this study revealed that MFCA is a useful tool to identify losses and inefficiencies of the production process. It is found that the factory is suffering from high losses due to material energy and system losses. In conclusion, it is calculated that system losses are the highest among all the losses due to inefficient use of available production capacity.
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In this paper has been building a statistical model of the Saudi financial market using GARCH models that take into account Volatility in prices during periods of circulation, were also study the effect of the type of random error distribution of the time series on the accuracy of the statistical model, as it were studied two types of statistical distributions are normal distribution and the T distribution. and found by application of a measured data that the best model for the Saudi market is GARCH (1,1) model when the random error distributed t. student's .
The utilization of sugarcane molasses (SCM), a byproduct of sugar refining, offers a promising bio-based alternative to conventional chemical admixtures in cementitious systems. This study investigates the effects of SCM at five dosage levels, 0.25%, 0.50%, 0.75%, 1.00%, and 1.25% by weight of cement, on cement mortar performance across fresh, mechanical, thermal, durability, and density criteria. A comprehensive experimental methodology was employed, including flow table testing, compressive strength (7, 14, and 28 days) and flexural strength measurements, embedded thermal sensors for real-time hydration monitoring, water absorption and chloride ion penetration tests, as well as 28-day density determination. Results revealed clear
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Self-driving automobiles are prominent in science and technology, which affect social and economic development. Deep learning (DL) is the most common area of study in artificial intelligence (AI). In recent years, deep learning-based solutions have been presented in the field of self-driving cars and have achieved outstanding results. Different studies investigated a variety of significant technologies for autonomous vehicles, including car navigation systems, path planning, environmental perception, as well as car control. End-to-end learning control directly converts sensory data into control commands in autonomous driving. This research aims to identify the most accurate pre-trained Deep Neural Network (DNN) for predicting the steerin
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Objective: The objective of the study was to test the hypothesis, that umbilical cord blood crude serum applied topically with its high concentration of growth factors may promote an early healing for animal models with burn injury.
Methods: Fresh human umbilical cord blood UCBS was collected and screened for transmitted diseases such as hepatitis B, hepatitis C and HIV. Mice and rabbits were scalded by boiling water and chemical burning by NaOH, then treated with UCBS. In comparison with a Cetrimide treated group and a control group (without treatment). The UCBS was subjected to microbial testing to demonstrate the presence or absence of extraneous viable contaminating microorganisms.
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Semiparametric methods combined parametric methods and nonparametric methods ,it is important in most of studies which take in it's nature more progress in the procedure of accurate statistical analysis which aim getting estimators efficient, the partial linear regression model is considered the most popular type of semiparametric models, which consisted of parametric component and nonparametric component in order to estimate the parametric component that have certain properties depend on the assumptions concerning the parametric component, where the absence of assumptions, parametric component will have several problems for example multicollinearity means (explanatory variables are interrelated to each other) , To treat this problem we use
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There are many aims of this book: The first aim is to develop a model equation that describes the spread of contamination through soils which can be used to determine the rate of environmental contamination by estimate the concentration of heavy metals (HMs) in soil. The developed model equation can be considered as a good representation for a problem of environmental contamination. The second aim of this work is to design two feed forward neural networks (FFNN) as an alternative accurate technique to determine the rate of environmental contamination which can be used to solve the model equation. The first network is to simulate the soil parameters which can be used as input data in the second suggested network, while the second network sim
... Show MoreRock mechanical properties are critical parameters for many development techniques related to tight reservoirs, such as hydraulic fracturing design and detecting failure criteria in wellbore instability assessment. When direct measurements of mechanical properties are not available, it is helpful to find sufficient correlations to estimate these parameters. This study summarized experimentally derived correlations for estimating the shear velocity, Young's modulus, Poisson's ratio, and compressive strength. Also, a useful correlation is introduced to convert dynamic elastic properties from log data to static elastic properties. Most of the derived equations in this paper show good fitting to measured data, while some equations show scatters
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