Breast cancer has got much attention in the recent years as it is a one of the complex diseases that can threaten people lives. It can be determined from the levels of secreted proteins in the blood. In this project, we developed a method of finding a threshold to classify the probability of being affected by it in a population based on the levels of the related proteins in relatively small case-control samples. We applied our method to simulated and real data. The results showed that the method we used was accurate in estimating the probability of being diseased in both simulation and real data. Moreover, we were able to calculate the sensitivity and specificity under the null hypothesis of our research question of being diseased or not.
Many carbonate reservoirs in the world show a tilted in originally oil-water contact (OOWC) which requires a special consideration in the selection of the capillary pressure curves and an understanding of reservoir fluids distribution while initializing the reservoir simulation models.
An analytical model for predicting the capillary pressure across the interface that separates two immiscible fluids was derived from reservoir pressure transient analysis. The model reflected the entire interaction between the reservoir-aquifer fluids and rock properties measured under downhole reservoir conditions.
This model retained the natural coupling of oil reservoirs with the aquifer zone and treated them as an explicit-region composite system
This study proposes a new version of the Autoregressive Integrated Moving Average (ARIMA) model using Artificial Neural Networks (ANNs) denoted by ARIMA-NN. The new model incorporates a multi-layer perceptron with matrix multiplication within a feed-forward network. The logistic, hyperbolic tangent (tanh), and sigmoid activation functions are used for weight updates in ARIMA-NN. A new forecasting algorithm is proposed, and one-step and multiple-steps forecasting procedures are rigorously analyzed. The proposed model was evaluated against existing forecasting model using performance metrics such as the Akaike Information Criterion (AIC) and Bayesian Information Criterion (
... Show MoreExperimental densities, viscosities η, and refractive indices nD data of the ternary ethanol+ n-hexane + 3-methyl pentane system have been determined at temperatures 293.15,303.15 and 313.15 K and at atmospheric pressure then these properties were calculated theoretically by using mixing rules for densities, viscosities and refractive indices .After that the theoretical data and the experimental data were compared due to the high relative errors in viscosities an equation of viscosity was proposed to decrease the relative errors.
Abstract: The aim of the research identify the effect of using the five-finger strategy in learning a movement chain on the balance beam apparatus for students in the third stage in the College of Physical Education and Sports Science, as well as to identify which groups (experimental and controlling) are better in learning the kinematic chain on the balance beam device, has been used The experimental approach is to design the experimental and control groups with pre-and post-test. The research sample was represented by third-graders, as the third division (j) was chosen by lot to represent the experimental group, and a division Third (i) to represent the control group, after which (10) students from each division were tested by lot to repr
... Show MorePareto distribution is used in many economic, financial and social applications. This distribution is used for the study of income and wealth and the study of settlement in cities and villages and the study of the sizes of oil wells as well as in the field of communication through the speed of downloading files from the Internet according to their sizes. This distribution is used in mechanical engineering as one of the distributions of models of failure, stress and durability. Given the practical importance of this distribution on the one hand, and the scarcity of sources and statistical research that deal with it, this research touched on some statistical characteristics such as derivation of its mathematical function , probability density
... Show MoreArabic language , like any other living languages grow and evolve ; social phenomenon
it is subject to the law of life ; therefore resemble organism also touted as the most eloquent
language and the ability to meet the needs of people in every time and place.
The contemplation of the verses of the Koran reveals a lot of means of expression
leading to the grammatical meaning of the social.
I have tried in this research that investigated the social meanings through the phenomena
of deletion and delivery delays and capture semantic landing through the meanings that lead
to psychological persuasion to comply with the orders after the rights of the divine in which
social directives.
It remains the greatest mystery o
The research deals with the concept of stigma as one of the important phenomena that cast a shadow over the nature of the individual, his being and his personality through the inferior view with which he confronts in society, and (Sartors) indicates in this regard that stigma may lead to negative discrimination that leads to many defects, in terms of obtaining On care, poor health, service, and frequent setbacks that can damage self-esteem. The first roots of this phenomenon go back to the Greek civilization and what the Greeks used to burn and cut off some parts of the body and then announce to the nation that the bearer of this sign is a criminal. In addition to the Arab peoples living from setbacks that contributed to the exacerbation
... Show MoreBotnet detection develops a challenging problem in numerous fields such as order, cybersecurity, law, finance, healthcare, and so on. The botnet signifies the group of co-operated Internet connected devices controlled by cyber criminals for starting co-ordinated attacks and applying various malicious events. While the botnet is seamlessly dynamic with developing counter-measures projected by both network and host-based detection techniques, the convention techniques are failed to attain sufficient safety to botnet threats. Thus, machine learning approaches are established for detecting and classifying botnets for cybersecurity. This article presents a novel dragonfly algorithm with multi-class support vector machines enabled botnet
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