A three species food web model involving a stage structure and cannibalism in the top predator species is proposed and studied. It is assumed that the prey species growth logistically in the absence of predator and the predation process occurred according to theLotka-Volterra functional response. The existence, uniqueness and bounded-ness of the solution of the model are investigated. The local and global stability conditions of all possible equilibrium points are established.The persistence conditions of the model are also determined. The local bifurcation near each of the equilibrium points is analyzed. The global dynamics of the model is investigated numerically and compared with the obtained analytical results. It is observed that the p

This study dealt with the basics of financial inclusion in terms of concept, importance and objectives, The empowerment of women financially and bank ,and then the relationship between financial inclusion and women, and determine the requirements of inclusion Financial resources for women. The analytical descriptive method was used for data, which included reviewing and analyzing information and data in economic and financial literature. The study: reached a number of conclusions, the most important of which are Financial inclusion contributes to women's financial and banking support, as there is a positive relationship between financial institutions Banking and women's access to financial and banking services, thus playing a rol

In this paper, we establish the conditions of the occurrence of the local bifurcations, such as saddle node, transcritical and pitchfork, of all equilibrium points of an eco-epidemiological model consisting of a prey-predator model with SI (susceptible-infected) epidemic diseases in prey population only and a refuge-stage structure in the predators. It is observed that there is a transcritical bifurcation near the axial and free predator equilibrium points, near disease-free equilibrium point is a saddle-node bifurcation and near positive (coexistence) equilibrium point is a saddle-node bifurcation, a transcritical bifurcation and a pitchfork bifurcation. Further investigations for Hopf bifurcation near coexistence equilibrium point

Background: Feeding is a complicated process that involves the coordination of cardiovascular, respiratory, gastrointestinal (GI), and oropharyngeal mechanisms, with support from the musculoskeletal and craniofacial systems. The practice of feeding could be correlated with eruption stage and nutritional status in infants. Aim of the study: This study aimed to assess the relation of feeding patterns to a selected oral variable (stage of the eruption of primary teeth) and growth parameters among clinically healthy infants. Subjects and Methods: A cross-sectional comparative study on a sample of (300) infants aged between 6 and 18 months was performed in Karbala City, Iraq. The feeding pattern was investigated using an information sheet ans

The current study aims to cover  the health topics  in the Iraqi  journalism ,  to know  the concern 's level  of the Iraqi journalism  when  covering  the health subjects and to know the size of its performance  under the diversity of  visual and audio medias. The researcher has discussed his research by wording it with a set of inquiries   that should be answered via the research and study.  He could have determined that by the following:

What is the concern's level of Iraqi journalism over the health subjects?  What are the forms and press arts that are functionalized by the Iraqi journalism as to get the health message to the republics?  What is t

One of the most important features of the Amazon Web Services (AWS) cloud is that the program can be run and accessed from any location. You can access and monitor the result of the program from any location, saving many images and allowing for faster computation. This work proposes a face detection classification model based on AWS cloud aiming to classify the faces into two classes: a non-permission class, and a permission class, by training the real data set collected from our cameras. The proposed Convolutional Neural Network (CNN) cloud-based system was used to share computational resources for Artificial Neural Networks (ANN) to reduce redundant computation. The test system uses Internet of Things (IoT) services through our ca

This work implements an Electroencephalogram (EEG) signal classifier. The implemented method uses Orthogonal Polynomials (OP) to convert the EEG signal samples to moments. A Sparse Filter (SF) reduces the number of converted moments to increase the classification accuracy. A Support Vector Machine (SVM) is used to classify the reduced moments between two classes. The proposed method’s performance is tested and compared with two methods by using two datasets. The datasets are divided into 80% for training and 20% for testing, with 5 -fold used for cross-validation. The results show that this method overcomes the accuracy of other methods. The proposed method’s best accuracy is 95.6% and 99.5%, respectively. Finally, from the results, it

In this paper, a handwritten digit classification system is proposed based on the Discrete Wavelet Transform and Spike Neural Network. The system consists of three stages. The first stage is for preprocessing the data and the second stage is for feature extraction, which is based on Discrete Wavelet Transform (DWT). The third stage is for classification and is based on a Spiking Neural Network (SNN). To evaluate the system, two standard databases are used: the MADBase database and the MNIST database. The proposed system achieved a high classification accuracy rate with 99.1% for the MADBase database and 99.9% for the MNIST database

One of the most important features of the Amazon Web Services (AWS) cloud is that the program can be run and accessed from any location. You can access and monitor the result of the program from any location, saving many images and allowing for faster computation. This work proposes a face detection classification model based on AWS cloud aiming to classify the faces into two classes: a non-permission class, and a permission class, by training the real data set collected from our cameras. The proposed Convolutional Neural Network (CNN) cloud-based system was used to share computational resources for Artificial Neural Networks (ANN) to reduce redundant computation. The test system uses Internet of Things (IoT) services th

The support vector machine, also known as SVM, is a type of supervised learning model that can be used for classification or regression depending on the datasets. SVM is used to classify data points by determining the best hyperplane between two or more groups. Working with enormous datasets, on the other hand, might result in a variety of issues, including inefficient accuracy and time-consuming. SVM was updated in this research by applying some non-linear kernel transformations, which are: linear, polynomial, radial basis, and multi-layer kernels. The non-linear SVM classification model was illustrated and summarized in an algorithm using kernel tricks. The proposed method was examined using three simulation datasets with different sample