The study was conducted out at the Ministry of Agriculture's Poultry Research Station/Animal ResourcesDepartment/Agricultural Research Center. To see how body weight (BW) and leptin hormone (LEP) levels inbreeder blood affect fertility and hatchability. 140 Iraqi local laying chickens (120 females + 20 males) aged 28weeks were used in the study. Following the numbering of The experiment was divided into three periods,each lasting 28 days, during which the breeder's live body weight was recorded and divided into two categories(greater than 1.5 kg and less than 1.5 kg), and blood samples were collected at the end of each period todetermine the concentration of leptin hormone in the breeders' blood. For comparison between mothers'performance, hormone concentration is separated into three groups: high, medium, and low, and according tothe interaction between body weight and leptin concentration to compare between mothers' performance.The results indicated a significant increase (p<0.05) in the concentration of cholesterol, high-density lipoprotein(HDL), low-density lipoprotein (LDL), very low-density lipoprotein (VLDL), and triglyceride (TG). Linearitybetween the studied traits and leptin concentration levels, by calculating the regression and correlationcoefficients, and adopting the hypothetical approach in estimating the prediction results to reach the bestpredictive values that approximate reality. We conclude from this study that body weight and theconcentration of leptin have unspecified effects on the serom chemical characteristics of laying hens.
Data mining has the most important role in healthcare for discovering hidden relationships in big datasets, especially in breast cancer diagnostics, which is the most popular cause of death in the world. In this paper two algorithms are applied that are decision tree and K-Nearest Neighbour for diagnosing Breast Cancer Grad in order to reduce its risk on patients. In decision tree with feature selection, the Gini index gives an accuracy of %87.83, while with entropy, the feature selection gives an accuracy of %86.77. In both cases, Age appeared as the most effective parameter, particularly when Age<49.5. Whereas Ki67 appeared as a second effective parameter. Furthermore, K- Nearest Neighbor is based on the minimu
... Show MoreNumeral recognition is considered an essential preliminary step for optical character recognition, document understanding, and others. Although several handwritten numeral recognition algorithms have been proposed so far, achieving adequate recognition accuracy and execution time remain challenging to date. In particular, recognition accuracy depends on the features extraction mechanism. As such, a fast and robust numeral recognition method is essential, which meets the desired accuracy by extracting the features efficiently while maintaining fast implementation time. Furthermore, to date most of the existing studies are focused on evaluating their methods based on clean environments, thus limiting understanding of their potential a
... Show MoreIn this paper, a new method of selection variables is presented to select some essential variables from large datasets. The new model is a modified version of the Elastic Net model. The modified Elastic Net variable selection model has been summarized in an algorithm. It is applied for Leukemia dataset that has 3051 variables (genes) and 72 samples. In reality, working with this kind of dataset is not accessible due to its large size. The modified model is compared to some standard variable selection methods. Perfect classification is achieved by applying the modified Elastic Net model because it has the best performance. All the calculations that have been done for this paper are in
Soil pH is one of the main factors to consider before undertaking any agricultural operation. Methods for measuring soil pH vary, but all traditional methods require time, effort, and expertise. This study aimed to determine, predict, and map the spatial distribution of soil pH based on data taken from 50 sites using the Kriging geostatistical tool in ArcGIS as a first step. In the second step, the Support Vector Machines (SVM) machine learning algorithm was used to predict the soil pH based on the CIE-L*a*b values taken from the optical fiber sensor. The standard deviation of the soil pH values was 0.42, which indicates a more reliable measurement and the data distribution is normal.
Diamond-like carbon, amorphous hydrogenated films forms of carbon, were pretreated from cyclohexane (C6H12) liquid using plasma jet which operates with alternating voltage 7.5kv and frequency 28kHz. The plasma Separates molecules of cyclohexane and Transform it into carbon nanoparticles. The effect of argon flow rate (0.5, 1 and 1.5 L/min) on the optical and chemical bonding properties of the films were investigated. These films were characterized by UV-Visible spectrophotometer, X-ray diffractometer (XRD) Raman spectroscopy and scanning electron microscopy (SEM). The main absorption appears around 296, 299 and 309nm at the three flow rate of argon gas. The value of the optical energy gap is 3.37, 3.55 and 3.68 eV at a different flow rate o
... Show MoreOil price forecasting has captured the attention of both researchers and academics because of the unique characteristics of crude oil prices and how they have a big impact on a lot of different parts of the economic value of the product. As a result, most academics use a lot of different ways to predict the future. On the other hand, researchers have a hard time because crude oil prices are very unpredictable and can be affected by many different things. This study uses support vector regression (SVR) with technical indicators as a feature to improve the prediction of the monthly West Texas Intermediate (WTI) price of crude oil. The root mean square error (RMSE), mean absolute error (MAE), and mean absolute percentage error (MAPE) measur
... Show MoreAutomatic speaker recognition may achieve remarkable performance in matched training and test conditions. Conversely, results drop significantly in incompatible noisy conditions. Furthermore, feature extraction significantly affects performance. Mel-frequency cepstral coefficients MFCCs are most commonly used in this field of study. The literature has reported that the conditions for training and testing are highly correlated. Taken together, these facts support strong recommendations for using MFCC features in similar environmental conditions (train/test) for speaker recognition. However, with noise and reverberation present, MFCC performance is not reliable. To address this, we propose a new feature 'entrocy' for accurate and robu
... Show MoreIn this paper, we develop the Hille and Nehari Type criteria for the oscillation of all solutions to the Fractional Differential Equations involving Conformable fractional derivative. Some new oscillatory criteria are obtained by using the Riccati transformations and comparison technique. We show the validity and effectiveness of our results by providing various examples.
Abstract: This research aims to investigate and analyze the most pressing issues facing the Iraqi economy, namely economic stability and inclusive growth Consequently, the present study investigates the effect of inflation and unemployment, which are significant contributors to economic instability, on inclusive growth dimensions such as GDP, education, health, governance, poverty, income inequality, and environmental performance. From 1991 to 2021, secondary data were collected using World Bank Indicators (WDI) and Organization for Economic Cooperation and Development (OECD) databases. The researchers also employed the autoregressive distributed lag (ARDL) model to determine the relationship between variables. The study revealed that fluct
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