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

Abstract: The international community now places significant emphasis on achieving zero carbon emissions, requiring both new researchers and experienced policymakers to prioritise this goal. This article examines the effects of carbon taxes, carbon cap and trade, renewable energy (RE) production and consumption, and economic growth (EG) on carbon emission reduction in the United States, Japan, Canada, and Australia. The study collected secondary data from the World Development Indicators (WDI) secondary source spanning the years 1991 to 2022. The study examines the relationship between variables using the cross-sectionally augmented autoregressive distributed lag (CS-ARDL) approach. The findings indicate that carbon taxes, carbon cap and tr

This study aims at discussing the theoretical and applicable parts of the reading comprehension to help the teachers of Arabic. This study shows that the students have a general weakness in reading comprehension. The researcher handles issues related to reading comprehension and to practicing exercises of the training strategies such as: dialogue, discussion, discussion questions, continuous training, group works. Such skills will be used to analyze a poem to see the level of the students’ reading comprehension and to develop the students’ skills. The study answers two questions:
1- What is the reading comprehension from a theoretical perspective?
2- How can we develop the skills of the reading comprehension from the practical

The aim of this study was ‎the‎ discrimination of Salmonella‎‎ isolated from chicken and their feed ‎and drinking water for the epidemiological control of salmonellosis. Totally, 289 samples, ‎including 217 chicken cloaca swabs, 46 water, and 26 feed samples were collected from five ‎different farms in Karbala governorate, Iraq. Conventional bacteriology tests, API 20E, Vitek 2, ‎and serology were used for bacterial identification. Random amplified polymorphic ‎DNA (RAPD)-polymerase chain reaction (PCR) was applied to analyze the genetic relationships ‎among Salmonella‎‎ isolates. The isolation rate of Salmonella‎‎ spp. was 21.1% (61/289). While the ‎water samples constituted the highest rate (30.4%), a rate of

Active Learning And Creative Thinking

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