The experiment was conducted at the Faculty of Agriculture University of Ain Shams-Egypt, from January to March 2008, to study the effect of different levels of chromium yeast (Cr-yeast) on broiler chickens performance, carcass quality and enzyme activity through 35 days of experimental periods. A total of 450 one-day old unsexed chickens (Cobb) strain were used. The birds were randomly allocated to five treatments with 3 replicates each. The treatments were control (T1) without supplementation and T2, T3, T4 and T5 which were supplemented with 0.5, 1, 1.5 and 2 mg Cr-yeast /kg diet, respectively. Live body weight and weight gain were significantly (p<0.05) higher when Cr-yeast were supplemented at 1 (T3), 1.5 (T4) and 2 (T5) mg/kg diet. Fe

The aim of the research is to identify the suitability of a patrol model in evaluating the financial performance of Iraqi banks. The financial reports of five Iraqi commercial banks were approved as a sample for research for the period from 2015 to 2020. The most common financial ratios were adopted for the purpose of measuring the five elements of the model, which are capital adequacy, profitability, credit risk, bankal efficiency and liquidity. The results showed the possibility of using the PATROL model in evaluating the performance of Iraqi banks, as it gave a realistic image of the reality of Iraqi banks in terms of high capital adequacy index and high liquidity, as well as fluctuation in profitability index, not to mention the prob

   A comparison of double informative and non- informative priors assumed for the parameter of Rayleigh distribution is considered. Three different sets of double priors are included, for a single unknown parameter of Rayleigh distribution. We have assumed three double priors: the square root inverted gamma (SRIG) - the natural conjugate family of priors distribution, the square root inverted gamma – the non-informative distribution, and the natural conjugate family of priors - the non-informative distribution as double priors .The data is generating form three cases from Rayleigh distribution for different samples sizes (small, medium, and large). And Bayes estimators for the parameter is derived under a squared erro

As a result of the significance of image compression in reducing the volume of data, the requirement for this compression permanently necessary; therefore, will be transferred more quickly using the communication channels and kept in less space in memory. In this study, an efficient compression system is suggested; it depends on using transform coding (Discrete Cosine Transform or bi-orthogonal (tap-9/7) wavelet transform) and LZW compression technique. The suggested scheme was applied to color and gray models then the transform coding is applied to decompose each color and gray sub-band individually. The quantization process is performed followed by LZW coding to compress the images. The suggested system was applied on a set of seven stand

Cancer is in general not a result of an abnormality of a single gene but a consequence of changes in many genes, it is therefore of great importance to understand the roles of different oncogenic and tumor suppressor pathways in tumorigenesis. In recent years, there have been many computational models developed to study the genetic alterations of different pathways in the evolutionary process of cancer. However, most of the methods are knowledge-based enrichment analyses and inflexible to analyze user-defined pathways or gene sets. In this paper, we develop a nonparametric and data-driven approach to testing for the dynamic changes of pathways over the cancer progression. Our method is based on an expansion and refinement of the pathway bei

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

This study was conducted in the poultry fields of the College of Agricultural Engineering Sciences / University of Baghdad from 10/15/2021 to 11/25/2021.To know the effect of adding different levels of Ganoderma lucidum to broiler diets on productive performance. 200 unsexed (Ross 308) chicks of one day age with a starting weight of (40) g were used. The chicks were randomly distributed into four treatments and 50 birds. One treatment included five replicates (10 birds/replicate), and the experimental treatments was as follows: T1, T2, T3, T4, and the percentages of adding reishi mushroom were 0, 0.5, 1, and 1.5 g/kg of feed, respectively, and the birds were fed on three starter diets, growth and final diets, The results of this stu