Diabetic retinopathy is an eye disease in diabetic patients due to damage to the small blood vessels in the retina due to high and low blood sugar levels. Accurate detection and classification of Diabetic Retinopathy is an important task in computer-aided diagnosis, especially when planning for diabetic retinopathy surgery. Therefore, this study aims to design an automated model based on deep learning, which helps ophthalmologists detect and classify diabetic retinopathy severity through fundus images. In this work, a deep convolutional neural network (CNN) with transfer learning and fine tunes has been proposed by using pre-trained networks known as Residual Network-50 (ResNet-50). The overall framework of the proposed

This research suggests a robust and systematic way for Arabic Sentiment Analysis using a vast dataset of 66,666 text reviews. One of the main advantages of this study is that the dataset was perfectly balanced (33,333 positive samples and 33,333 negative samples). In machine learning, this 50/50 split is important because it eliminates class bias and enables the predictive model to treat both sentiment classes equally. As shown in the values of the metrics — overall accuracy, weighted precision, weighted recall, and F1 score — there is great similarity among them, indicating a stable and reliable assessment of the model's real potential throughout the Arabic dataset. Based on data profile, the average word count per review is 42.3

This paper offers a systemic review of the deep learning methods to detect violence on campus, which is a critical issue in intelligent surveillance to improve the student safety and prompt cut off of violent accidents. The review reviews studies published 2018-2025, concentrating on model structure to detect fights, bullying, vandalism, and aggressive behavior on problematic campuses due to occlusion and light variations and complicated human interactions. The research design includes a comparative study of different deep learning networks, such as CNNs, RNNs, 3D CNNs, attention-based networks, transformers, graph neural networks, neuro-fuzzy, and multimodal systems and federated learning methods. The paper also assesses benchmark

Objectives: With the advent of ongoing novel modalities toward the treatment of human epidermal growth factor receptor 2 (HER2)/NEU - positive malignancies, the serious side effects of chemoradiotherapy have been minimized. Hence, this study was conducted to identify the patterns of immunohistochemical expression of the promising therapeutic target (HER2/NEU) among Iraqi patients with medulloblastoma in an attempt to provide basic histological information’s that would help in future clinical researches.Materials and Methods: In this retrospective study, 42 formalin - fixed paraffin - embedded tissue blocks represent cases of surgically removed medulloblastomas were retrieved from the archived materials in a specialized surgical ho

The present study is carried out to identify the algae in the groundwater of the three areas of Tikrit city, including (the center of Tikrit , the region of AL-Jazira , Awainat village) by nine wells, a depths ranged between 9 meter at well 8 and 110 meter at wells 3 and 5 . And examined the environmental characteristics of physical, chemical and biological factors during the study period from September 2009 to June 2010. It is obtained that wells in the study area is lower alkalinity, average it ranged (6.448-7.418). It was noted that the values of the dissolved oxygen are few and almost non-existent in some cases it ranged between (6.5-6.3)mg/l , analysis of biological oxygen demand refers to wells water (clean- very clean) average