UML (Unfiled Modeling Language), known as the standard method for object-oriented (analysis and design) modeling, includes other languages which enables it to implement a prototype of the structure and behaviors of the product. This paper attempts to explore the observations about UML role on the cost of software maintenance, and hence on the Total Cost of Ownership (TCO) of a software product. It is therefore important to investigate the benefits obtained through modeling..

 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

Abstract The current study is a theoretical study that aims to underline the role of picture books as a serious genre of children's literature in raising children's understanding of English literature and life concepts; especially for non-English speakers. Unfortunately, most Iraqi people have developed a social phobia of learning English since childhood. This phobia is resulted from the heavy traditional reading and writing assignments as well as hard exams. Therefore, this study suggests incorporating more interesting literary material like picture books that would bring pleasure and help in raising children's love and cognition of English Language. More significantly, it calls to replace the old curriculum with a more vital

A series of coumarin derivatives linked to amino acid ester side chains were synthesized and evaluated of their antibacterial and antifungal activity. The coumarin derivatives was alkylated by the ethyl bromoacetate and then using potassium carbonate to get alkylated hymecromone. Conventional solution method for amide bond formation was used as a coupling method between the carboxy-protected amino acids with acetic acid side chain of coumarin derivatives. The DCC/ HOBt coupling reagents were used for peptide bond formation. The proposed analogues were successfully synthesized and their structural formulas were consistent with the proposed struct

To date, comprehensive reviews and discussions of the strengths and limitations of Remote Sensing (RS) standalone and combination approaches, and Deep Learning (DL)-based RS datasets in archaeology have been limited. The objective of this paper is, therefore, to review and critically discuss existing studies that have applied these advanced approaches in archaeology, with a specific focus on digital preservation and object detection. RS standalone approaches including range-based and image-based modelling (e.g., laser scanning and SfM photogrammetry) have several disadvantages in terms of spatial resolution, penetrations, textures, colours, and accuracy. These limitations have led some archaeological studies to fuse/integrate multip

Sorting and grading agricultural crops using manual sorting is a cumbersome and arduous process, in addition to the high costs and increased labor, as well as the low quality of sorting and grading compared to automatic sorting. the importance of deep learning, which includes the artificial neural network in prediction, also shows the importance of automated sorting in terms of efficiency, quality, and accuracy of sorting and grading. artificial neural network in predicting values and choosing what is good and suitable for agricultural crops, especially local lemons.

Diagnosing heart disease has become a very important topic for researchers specializing in artificial intelligence, because intelligence is involved in most diseases, especially after the Corona pandemic, which forced the world to turn to intelligence. Therefore, the basic idea in this research was to shed light on the diagnosis of heart diseases by relying on deep learning of a pre-trained model (Efficient b3) under the premise of using the electrical signals of the electrocardiogram and resample the signal in order to introduce it to the neural network with only trimming processing operations because it is an electrical signal whose parameters cannot be changed. The data set (China Physiological Signal Challenge -cspsc2018) was ad

The deep learning algorithm has recently achieved a lot of success, especially in the field of computer vision. This research aims to describe the classification method applied to the dataset of multiple types of images (Synthetic Aperture Radar (SAR) images and non-SAR images). In such a classification, transfer learning was used followed by fine-tuning methods. Besides, pre-trained architectures were used on the known image database ImageNet. The model VGG16 was indeed used as a feature extractor and a new classifier was trained based on extracted features.The input data mainly focused on the dataset consist of five classes including the SAR images class (houses) and the non-SAR images classes (Cats, Dogs, Horses, and Humans). The Conv