Active Learning And Creative Thinking

The research aimed at designing teaching program using jigsaw in learning spiking in volleyball as well as identifying the effect of these exercises on learning spring in volleyball. The researchers used the experimental method on (25) students as experimental group and (27) students as controlling group and (15) students as pilot study group. The researchers conducted spiking tests then the data was collected and treated using proper statistical operations to conclude that the strategy have a positive effect in experimental group. Finally, the researchers recommended using the strategy in making similar studies on other subjects and skills.

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

In the recent years, remote sensing applications have a great interest because it's offers many advantages, benefits and possibilities for the applications that using this concept, satellite it's one must important applications for remote sensing, it's provide us with multispectral images allow as study many problems like changing in ecological cover or biodiversity for earth surfers, and illustrated biological diversity of the studied areas by the presentation of the different areas of the scene taken depending on the length of the characteristic wave, Thresholding it's a common used operation for image segmentation, it's seek to extract a monochrome image from gray image by segment this image to two region (for

Maximizing the net present value (NPV) of oil field development is heavily dependent on optimizing well placement. The traditional approach entails the use of expert intuition to design well configurations and locations, followed by economic analysis and reservoir simulation to determine the most effective plan. However, this approach often proves inadequate due to the complexity and nonlinearity of reservoirs. In recent years, computational techniques have been developed to optimize well placement by defining decision variables (such as well coordinates), objective functions (such as NPV or cumulative oil production), and constraints. This paper presents a study on the use of genetic algorithms for well placement optimization, a ty

This research focused on clarifying the relationship strategic decisions for operations management & performance excellence organizational, The research emerges from a problem which explained by many application questions. Special questionnaire has been prepared for this purpose distributed (72) to sample of  management levels (Top, middle) in the General company for mining industries and aquatic Insullation & the General company of batteries industry, The research has tried to test a number hypotheses related to the relation and regression among the variables of the research, and the differences among the <

Introduction: Methadone hydrochloride (MDN) is an effective pharmacological substitution treatment for opioids dependence, adopted in different countries as methadone maintenance treatment (MMT) programmes. However, MDN can exacerbate the addiction problem if it is abused and injected intravenously, and the frequent visits to the MMT centres can reduce patient compliance. The overall aim of this study is to develop a novel extended-release capsule of MDN using the sol-gel silica (SGS) technique that has the potential to counteract medication-tampering techniques and associated health risks and reduce the frequent visits to MMT centres. Methods: For MDN recrystallisation, a closed container method (CCM) and hot-stage method (HSM) were conduc

BCl3 is toxic gas and its detection is of great importance. Thus, here, B3LYP, M06-2X, and B97D density functionals are utilized for probing the effect of decorating Zn, Cd, and Au on the sensing performance of an AlP nano-sheet (AlPNS) in detecting the BCl3. We predict that the interaction of pure AlPNS with BCl3 is physisorption, and the sensing response (SR) of AlPNS is approximately 9.2. The adsorption energy of BCl3 changes from −4.1 to −18.8, −19.1, and −19.5 kcal/mol by decorating the Zn, Cd, and Au metals into the AlPNS surface, respectively. Also, the corresponding SR meaningfully rises to 40.4, 59.0, and 80.9, indicating that by increasing the atomic number of metals, the sensitivity of metal decorated AlPNS (metal@AlPNS)