The current research aims to examine the effect of the rapid learning method in developing creative thinking among second-grade female students in the subject of history. Thus, the researcher has adopted an experimental design of two groups to suit the nature of the research. The sample of the study consists of (36) randomly selected students from Al-Shafaq Secondary School for Women, which are divided randomly into two groups. The first group represents the experimental; it includes (31) students who studied the subject of history using the quick learning method. The second group, on the other hand, is the control group, which consists of (32) students, who studied the same subject using the traditional way. Before starting with the exp

This study aimed to improve the microencapsulation technique using a type coating the encapsulation Layer by Layer, which provide the best protection for life Lactobacillus casei in the extrusion method and use the microencapsulation of materials of the protein concentrated by protein 80% and the coating with alginate and chitosan have the results showed the variation in the difference of the binding process encapsulation yield among the types of coating through. by studying of these the effect o stability of the bio probiotic free cell and the three types coated towards three different concentrations from bile salts 0, 0.3, 0.5 and 0.7% when the periods of time different of zero and two and three hours at incubation the recorded

The paper aims to propose Teaching Learning based Optimization (TLBO) algorithm to solve 3-D packing problem in containers. The objective which can be presented in a mathematical model is optimizing the space usage in a container. Besides the interaction effect between students and teacher, this algorithm also observes the learning process between students in the classroom which does not need any control parameters. Thus, TLBO provides the teachers phase and students phase as its main updating process to find the best solution. More precisely, to validate the algorithm effectiveness, it was implemented in three sample cases. There was small data which had 5 size-types of items with 12 units, medium data which had 10 size-types of items w

With the rapid development of smart devices, people's lives have become easier, especially for visually disabled or special-needs people. The new achievements in the fields of machine learning and deep learning let people identify and recognise the surrounding environment. In this study, the efficiency and high performance of deep learning architecture are used to build an image classification system in both indoor and outdoor environments. The proposed methodology starts with collecting two datasets (indoor and outdoor) from different separate datasets. In the second step, the collected dataset is split into training, validation, and test sets. The pre-trained GoogleNet and MobileNet-V2 models are trained using the indoor and outdoor se

The study aimed to reveal the level of knowledge and tendencies of high- study students specializing in curriculum and teaching methods at King Khalid University towards harmonious strategies with brain-based learning (BBL). And Then, putting a proposed concept to develop knowledge and tendencies of high-study students specializing in curriculum and teaching methods at King Khalid University towards harmonious strategies with Brain-based learning (BBL). For achieving this goal, a cognitive test and a scale of tendency were prepared to apply harmonious strategies with brain-based learning. The descriptive approach was used because it suits the goals of the study. The study sample consisted of (70) male and female students of postgraduate

 An oil spill is a leakage of pipelines, vessels, oil rigs, or tankers that leads to the release of petroleum products into the marine environment or on land that happened naturally or due to human action, which resulted in severe damages and financial loss. Satellite imagery is one of the powerful tools currently utilized for capturing and getting vital information from the Earth's surface. But the complexity and the vast amount of data make it challenging and time-consuming for humans to process. However, with the advancement of deep learning techniques, the processes are now computerized for finding vital information using real-time satellite images. This paper applied three deep-learning algorithms for satellite image classification

Cassava, a significant crop in Africa, Asia, and South America, is a staple food for millions. However, classifying cassava species using conventional color, texture, and shape features is inefficient, as cassava leaves exhibit similarities across different types, including toxic and non-toxic varieties. This research aims to overcome the limitations of traditional classification methods by employing deep learning techniques with pre-trained AlexNet as the feature extractor to accurately classify four types of cassava: Gajah, Manggu, Kapok, and Beracun. The dataset was collected from local farms in Lamongan Indonesia. To collect images with agricultural research experts, the dataset consists of 1,400 images, and each type of cassava has

Background: The efficacy of educational strategies is crucial for nursing students to competently perform pediatric procedures like nasogastric tube insertion. Specific Background: This study evaluates the effectiveness of simulation, blended, and self-directed learning strategies in enhancing these skills among nursing students. Knowledge Gap: Previous research lacks a comprehensive comparison of these strategies' impacts on skill development in pediatric nursing contexts. Aims: The study aims to assess the effectiveness of different educational strategies on nursing students' ability to perform pediatric nasogastric tube insertions. Methods: A pre-experimental design was employed at the College of Nursing, University of Baghdad, i