The convolutional neural networks (CNN) are among the most utilized neural networks in various applications, including deep learning. In recent years, the continuing extension of CNN into increasingly complicated domains has made its training process more difficult. Thus, researchers adopted optimized hybrid algorithms to address this problem. In this work, a novel chaotic black hole algorithm-based approach was created for the training of CNN to optimize its performance via avoidance of entrapment in the local minima. The logistic chaotic map was used to initialize the population instead of using the uniform distribution. The proposed training algorithm was developed based on a specific benchmark problem for optical character recog

HR Ghanim, GA Abdulhassan, International Journal of Early Childhood Special Education, 2022

The aim of the current research is to identify the effect of the active thinking model in the achievement of students of the fifth grade applied science of physics, and their pivotal thinking by verifying the two zero hypotheses, where there is no significant difference at the level of significance (0.05) between the average scores of the experimental group who studied physics using the active thinking model and the average scores of the control group students who studied the same material in the usual way in the achievement test, as well as in the pivotal thinking test. The research sample consisted of (77) students of the applied fifth grade students in two divisions (a) and (b), randomly selected (a) to be the experimental group, and (b)

Artificial Neural Networks (ANN) is one of the important statistical methods that are widely used in a range of applications in various fields, which simulates the work of the human brain in terms of receiving a signal, processing data in a human cell and sending to the next cell. It is a system consisting of a number of modules (layers) linked together (input, hidden, output). A comparison was made between three types of neural networks (Feed Forward Neural Network (FFNN), Back propagation network (BPL), Recurrent Neural Network (RNN). he study found that the lowest false prediction rate was for the recurrentt network architecture and using the Data on graduate students at the College of Administration and Economics, Univer

When optimizing the performance of neural network-based chatbots, determining the optimizer is one of the most important aspects. Optimizers primarily control the adjustment of model parameters such as weight and bias to minimize a loss function during training. Adaptive optimizers such as ADAM have become a standard choice and are widely used for their invariant parameter updates' magnitudes concerning gradient scale variations, but often pose generalization problems. Alternatively, Stochastic Gradient Descent (SGD) with Momentum and the extension of ADAM, the ADAMW, offers several advantages. This study aims to compare and examine the effects of these optimizers on the chatbot CST dataset. The effectiveness of each optimizer is evaluat

To approach the problem of individual oppression with an international perspective drawing on Foucauldian concepts, this paper compares George Orwell’s 1984 (1949) and the Iraqi Sinan Antoon’s I’jaam (2004), which was translated into English in 2007. Even though Orwell and Antoon come from dissimilar cultural backgrounds, religions and epochs, they have tackled the issue of individuals’ oppression through their oppressed characters in a strikingly similar way. Hence, by applying the theories of both the American School of Comparative Literature and Foucauldian concepts, the current study attempts to establish a relationship between the Western and Eastern ways of dealing with the issue of oppression as an international problem in au

Lung cancer is the most common dangerous disease that, if treated late, can lead to death. It is more likely to be treated if successfully discovered at an early stage before it worsens. Distinguishing the size, shape, and location of lymphatic nodes can identify the spread of the disease around these nodes. Thus, identifying lung cancer at the early stage is remarkably helpful for doctors. Lung cancer can be diagnosed successfully by expert doctors; however, their limited experience may lead to misdiagnosis and cause medical issues in patients. In the line of computer-assisted systems, many methods and strategies can be used to predict the cancer malignancy level that plays a significant role to provide precise abnormality detectio

Pricing has an important position among the elements of marketing mixture (4ps) as it represents revenues that in turn represent one of the important  pillars' for resources affecting on organizations sustainability and development , and the failure in determining prices and their strategies has a dangerous effect on the organizations reality and future as a whole . from this point,  this is what from the focus of the research problem,which centered on how to get companies to critical price that satisfies customers and achieve corporate objectives.