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 Convolutional Neural Network (CNN) has been chosen as a better option for the training process because it produces a high accuracy. The final accuracy has reached 91.18% in five different classes. The results are discussed in terms of the probability of accuracy for each class in the image classification in percentage. Cats class got 99.6 %, while houses class got 100 %.Other types of classes were with an average score of 90 % and above.
Reduction of noise and vibration in spur gear experimentally by using asymmetric teeth profiles with tip relief was presented. Both of classical (symmetric) and asymmetric (with and without tip relief) spur gears are used in this work. Gear test rig was constructed to achieve torsional vibration measuring, and two modified cutters are designed and manufactured to achieve tooth profile modifications. First to cut asymmetric gear tooth with pressure angles (14.5o/25 o) without tip relief for loaded and unloaded tooth sides respectively, and second to cut asymmetric gear tooth with pressure angles (14.5o/25 o) for loaded and unloaded tooth sides respectively with tip relief to ach
... Show MoreIn current study a computation fluid dynamic (CFD) technique was used to investigate the effect of groynes shape and spacing on the scour pattern and the maximum scour depth in open channel flow. CFD model have been validated throughout comparing the numerical results with three previous experimental studies for a single groyne located in open channel with three different shapes (L, quadrant, and parabola shapes). The comparison revealed very good agreement between numerical results of the maximum scour depth with the results of all experimental models. Moreover, investigations of the effect of multi-groynes (three groynes and four groynes) arranged in parallel with constant spacing and also with variable spacing have been done, the
... Show MoreQuantum dots (QDs) can be defined as nanoparticles (NPs) in which the movement of charge carriers is restricted in all directions. CdTe QDs are one of the most important semiconducting crystals among other various types where it has a direct energy gap of about 1.53 eV. The aim of this study is to exaine the optical and structural properties of the 3MPA capped CdTe QDs. The preparation method was based on the work of Ncapayi et al. for preparing 3MPA CdTe QDs, and hen, the same way was treated as by Ahmed et al. via hydrothermal method by using an autoclave at the same temperature but at a different reaction time. The direct optical energy gap of CdTe QDs is between 2.29 eV and 2.50 eV. The FTIR results confirmed the covalent bonding betwee
... Show MoreThe study aimed to determine the effect of the flipped learning model in improving the acquisition of the overhand serve skill in volleyball among second-year students at the College of Physical Education and Sport Sciences, University of Baghdad, for the academic year 2024/2025. The study used an experimental design with a control group and pre-post testing, on a purposive sample consisting of 12 students. The model relied on watching short videos before class via the SGS application, and practical application in class at a rate of three sessions per week. The results showed a significant improvement in performance, as the calculated value (t = 5.356) exceeded the tabulated value (2.042) at a significance level of 0.05. The percentage of s
... Show MoreBackground: Unlike normal EEG patterns, the epileptiform abnormal pattern is characterized by different mor phologies such as the high-frequency oscillations (HFOs) of ripples on spikes, spikes and waves, continuous and sporadic spikes, and ploy2 spikes. Several studies have reported that HFOs can be novel biomarkers in human epilepsy study. S) Method: To regenerate and investigate these patterns, we have proposed three large scale brain network models (BNM by linking the neural mass model (NMM) of Stefanescu-Jirsa 2D (S-J 2D) with our own structural con nectivity derived from the realistic biological data, so called, large-scale connectivity connectome. These models include multiple network connectivity of brain regions at different
... Show Moreأولاً: مشكلة البحث:
للتربية دوراً أساسياً في تكوين الإنسان ليصبح قادراً على الإسهام الحضاري، ودفع عجلة التنمية إلى الأمام. وينظر للتربية حالياً بأنها عملية توثيق الصلة بين الناشئ والبيئة في ظروف معينة تعينه على النمو في الاتجاه المرغوب فيه. ويأتي الجانب المعرفي في مقدمة جوانب النمو، فهو المسؤول عن بناء شخصية الفرد وأسلوب تفكيره (سعيد، 1989، ص28). فضلاً عن كونه الخاصية الراقية عند الإنسان التي
... Show MoreWith the fast-growing of neural machine translation (NMT), there is still a lack of insight into the performance of these models on semantically and culturally rich texts, especially between linguistically distant languages like Arabic and English. In this paper, we investigate the performance of two state-of-the-art AI translation systems (ChatGPT, DeepSeek) when translating Arabic texts to English in three different genres: journalistic, literary, and technical. The study utilizes a mixed-method evaluation methodology based on a balanced corpus of 60 Arabic source texts from the three genres. Objective measures, including BLEU and TER, and subjective evaluations from human translators were employed to determine the semantic, contextual an
... Show MoreThe multi-focus image fusion method can fuse more than one focused image to generate a single image with more accurate description. The purpose of image fusion is to generate one image by combining information from many source images of the same scene. In this paper, a multi-focus image fusion method is proposed with a hybrid pixel level obtained in the spatial and transform domains. The proposed method is implemented on multi-focus source images in YCbCr color space. As the first step two-level stationary wavelet transform was applied on the Y channel of two source images. The fused Y channel is implemented by using many fusion rule techniques. The Cb and Cr channels of the source images are fused using principal component analysis (PCA).
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