Abstract

   Suffering the human because of pressure normal life of exposure to several types of heart disease as a result of due to different factors. Therefore, and in order to find out the case of a death whether or not, are to be modeled using binary logistic regression model

    In this research used, one of the most important models of nonlinear regression models extensive use in the modeling of applications statistical, in terms of heart disease which is the binary logistic regression model. and then estimating the parameters of this model using the statistical estimation methods, another problem will be appears in estimating its parameters, as well as when the numbe

      A model using the artificial neural networks and genetic algorithm technique is developed for obtaining optimum dimensions of the foundation length and protections of small hydraulic structures. The procedure involves optimizing an objective function comprising a weighted summation of the state variables. The decision variables considered in the optimization are the upstream and downstream cutoffs lengths and their angles of inclination, the foundation length, and the length of the downstream soil protection. These were obtained for a given maximum difference in head, depth of impervious layer and degree of anisotropy. The optimization carried out is subjected to constraints that ensure a safe structure aga

The habitat type and food availability always influence the population size of many
organisms. Bird’s feeding pattern should be abstracted to complete avian community structure
data. The agronomy main research farm of Orissa University of Agriculture and Technology
is a well-managed multi-crop agro-ecosystem which provides a suitable ground for ecological
research. In a multi-crop farmland, the association of Barn Swallow Hirundo rustica Linnaeus,
1758, with the Indian mustard Brassica juncea (L.) Czernajew, 1859 crops have been
recorded for the first time while hovering only on this field. A flock of Barn swallows was
recorded in 32 field visits while flying continuously over the Indian mustard field after
flow

In this research, Mn-doped TiO2 thin films were grown on glass, Si and OIT/glass substrates by R.F magnetron sputtering technique with thicknesses (250 nm) using TiO2:Mn target under Ar gas pressure and power of 100 Watt. Through the results of X-ray diffraction, the prepared thin films are of the polycrystallization type after the process of annealing at 600°C for two hour The average crystalline size were 145.32, 280.97 and 261.23 nm for (TiO2:Mn) thin film on glass, Si and OIT/glass substrates respectively, while the measured surface roughness is between 0.981nm and 1.14 nm. The fabricated (TiO2:Mn) thin film on glass sensors have high sensitivity for hydrogen( H2 reducing gas) compared to the sensitivity for hydrogen gas on Si and OIT/

Water quality sensors have recently received a lot of attention due to their impact on human health. Due to their distinct features, environmental sensors are based on carbon quantum dots (CQDs). In this study, CQDs were prepared using the electro-chemical method, where the structural and optical properties were studied. These quantum dots were used in the environmental sensor application after mixing them with three different materials: CQDs, Alq3 polymer and CQDs and Alq3 solutions using two different methods: drop casting and spin coating, and depositing them on silicon. The sensitivity of the water pollutants was studied for each case of the prepared samples after measuring the change in resistance of the samples at a temperature of

<p>Currently, breast cancer is one of the most common cancers and a main reason of women death worldwide particularly in<strong> </strong>developing countries such as Iraq. our work aims to predict the type of tumor whether benign or malignant through models that were built using logistic regression and neural networks and we hope it will help doctors in detecting the type of breast tumor. Four models were set using binary logistic regression and two different types of artificial neural networks namely multilayer perceptron MLP and radial basis function RBF. Evaluation of validated and trained models was done using several performance metrics like accuracy, sensitivity, specificity, and AUC (area under receiver ope

في البداية اود الاشارة الى ان فهم حقيقة الازمة هو ذو جانب فني يتعلق بالجينات الوراثية لنظام يملك في احيناته قدرة عالية على تفريخ المشتقات. هذا النظام الذي يزداد عقما وتدميرا يزداد قدرة على خلق النقود الائتمانية/المشتقات، وكلما اقتربنا اكثر من فهم هذا الجانب كلما اسقطت في ايدينا تلك التوصيفات الاكاديمية الجاهزة في نقص الرقابة والاشراف، تركيز المخاطر،....الخ التي تناولتها الكتابات الشائعة في معظم طروحات