In this article, Convolution Neural Network (CNN) is used to detect damage and no damage images form satellite imagery using different classifiers. These classifiers are well-known models that are used with CNN to detect and classify images using a specific dataset. The dataset used belongs to the Huston hurricane that caused several damages in the nearby areas. In addition, a transfer learning property is used to store the knowledge (weights) and reuse it in the next task. Moreover, each applied classifier is used to detect the images from the dataset after it is split into training, testing and validation. Keras library is used to apply the CNN algorithm with each selected classifier to detect the images. Furthermore, the performa

Computer-aided diagnosis (CAD) has proved to be an effective and accurate method for diagnostic prediction over the years. This article focuses on the development of an automated CAD system with the intent to perform diagnosis as accurately as possible. Deep learning methods have been able to produce impressive results on medical image datasets. This study employs deep learning methods in conjunction with meta-heuristic algorithms and supervised machine-learning algorithms to perform an accurate diagnosis. Pre-trained convolutional neural networks (CNNs) or auto-encoder are used for feature extraction, whereas feature selection is performed using an ant colony optimization (ACO) algorithm. Ant colony optimization helps to search for the bes

The intelligent buildings provided various incentives to get highly inefficient energy-saving caused by the non-stationary building environments. In the presence of such dynamic excitation with higher levels of nonlinearity and coupling effect of temperature and humidity, the HVAC system transitions from underdamped to overdamped indoor conditions. This led to the promotion of highly inefficient energy use and fluctuating indoor thermal comfort. To address these concerns, this study develops a novel framework based on deep clustering of lagrangian trajectories for multi-task learning (DCLTML) and adding a pre-cooling coil in the air handling unit (AHU) to alleviate a coupling issue. The proposed DCLTML exhibits great overall control and is

Goal  of  research  is  to  investigate  the  impact  of the  use  of  effective  learning  model in the  collection  of  the  fourth  grade  students/Department of  physics in the material  educational methods  and the  development  of  critical thinking  .to teach  this goal  has  been  formulated  hypothesis cefereeten zero  subsidiary  of the second hypothesis  .To  investigate  the  research  hypothesis  were  selected  sample  of  fourth-grade  students of the  department  of physics at the univers

       The present study aimed to identify the learning gap between classroom-based education and artificial intelligence (AI)-based education among students of Colleges of Physical Education and Sports Sciences. It also sought to determine the effectiveness of classroom education and AI-based education in reducing the learning gap among these students. The research problem addressed the following questions: Are there statistically significant differences in the learning gap between students who learn through traditional classroom education and those who learn through AI-based education in Colleges of Physical Education and Sports Sciences? What is the nature of the learning gap between classroom education and AI-based educati

The research aimed at identifying the effect of the think, pair, and share strategy by using educational movies on learning jumping opened legs and closed legs skills on vault in artistic gymnastics for women. It also aimed at identifying the group that learned better the skills understudy. The researcher used the experimental method on second-grade College of Physical Education and Sport Sciences female students. Twelve female students were selected from each of the two sections to form the subjects of the study. The main program was applied for eight weeks with one learning session per week. The data was collected and treated using SPSS to conclude that the think, pair, and share strategy and the traditional program have positive effects

Evaluation of “Holy Quran & Islamic Education” Curriculum for Second Intermediate Stage from Perspectives of Teachers & Supervisors of material A Field Study conducted in the Directorates-General of Education in Baghdad Governorate. It goes without saying that educational curricula for students of all stages of schooling are in bad need of reviewing, evaluation and revision. The Islamic education curriculum is no exception, since it is a basic subject that plays a role in developing the individual’s moral and conscientious aspects, promotes his/her inner discipline and helps establish coherence with the values system of the community to which he/she belongs.

Based on the foregoing, the evaluation process of

BP algorithm is the most widely used supervised training algorithms for multi-layered feedforward neural net works. However, BP takes long time to converge and quite sensitive to the initial weights of a network. In this paper, a modified cuckoo search algorithm is used to get the optimal set of initial weights that will be used by BP algorithm. And changing the value of BP learning rate to improve the error convergence. The performance of the proposed hybrid algorithm is compared with the stan dard BP using simple data sets. The simulation result show that the proposed algorithm has improved the BP training in terms of quick convergence of the solution depending on the slope of the error graph.