Automated detection of Dubas palm infestation by image processing techniques has practical significance as it can improve agricultural efficiency, increase crop yield and quality, protect the environment, and provide data-driven insights. It also reduces the human effort required for pest control and enhances sustainability. In this study, we aimed to automate the detection of Dubas bug infestation in palm trees using deep learning with transfer learning residual neural networks. Based on four models: InceptionResNetV2, ResNet18, ResNet50, and ResNet101, the data used in this study were obtained by drone photography, many images were taken, and then the infected area was extracted. Using two types of data, 185 infected images and 185 healthy images were extracted. Through analyzing the results, we reached a conclusion regarding the automated detection of Dubas bug infestations. In palm trees, ResNet18 and ResNet50 are the most reliable models. © The Author(s).
This article proposes a new technique for determining the rate of contamination. First, a generative adversarial neural network (ANN) parallel processing technique is constructed and trained using real and secret images. Then, after the model is stabilized, the real image is passed to the generator. Finally, the generator creates an image that is visually similar to the secret image, thus achieving the same effect as the secret image transmission. Experimental results show that this technique has a good effect on the security of secret information transmission and increases the capacity of information hiding. The metric signal of noise, a structural similarity index measure, was used to determine the success of colour image-hiding t
... Show MoreIn this research, silver nanoparticles (AgNPs) were manufactured using aqueous extract of mushroom Pleurotus ostreatus. Anticancer potential of AgNPs was investigated versus human breast cancer cell line (MCF-7). Cytotoxic response was assessed by MTT assay. AgNPs showed inhibition effect at the following concentrations 12.5, 25, 50, 100 and 200 µg/ml versus MCF-7 cell line, and all treatments had a positive result. The MCF-7 cells were inhibited up to 85.14 % at the concentration 200 μg/ml of AgNPs which reduced cells viability to 14.86%, while 12.5 μg/ml of AgNPs caused 24.23% cells inhibition with reduction of cells viability to 75.77%.
Laboratory studies were conducted at the biological control unit, college of Agriculture, University of Baghdad to evaluate some biological aspects of the predator Chilocorus bipustulatus (Coleoptera: Coccinellidae), which is considered one of the most important predators on many insect pests, especially the scale insect, Parlatoria blanchardi, (Homoptera: Diaspididae) on date palms. The results showed that biological parameters of the predator were varied according to different degree of temperature. Egg incubation period was significantly different and reached to 7.5 and 5.44 day at 25 and 30°C respectively, Fertility was the same 100% at both temperature degrees. Larval growth periods were 17.41 and 16.12 day as well as the mortality du
... Show MoreThe emergence of COVID-19 has resulted in an unprecedented escalation in different aspects of human activities, including medical education. Students and educators across academic institutions have confronted various challenges in following the guidelines of protection against the disease on one hand and accomplishing learning curricula on the other hand. In this short view, we presented our experience in implementing e-learning to the undergraduate nursing students during the present COVID-19 pandemic emphasizing the learning content, barriers, and feedback of students and educators. We hope that this view will trigger the preparedness of nursing faculties in Iraq to deal with this new modality of learning and improve it should t
... Show MoreMachine learning (ML) is a key component within the broader field of artificial intelligence (AI) that employs statistical methods to empower computers with the ability to learn and make decisions autonomously, without the need for explicit programming. It is founded on the concept that computers can acquire knowledge from data, identify patterns, and draw conclusions with minimal human intervention. The main categories of ML include supervised learning, unsupervised learning, semisupervised learning, and reinforcement learning. Supervised learning involves training models using labelled datasets and comprises two primary forms: classification and regression. Regression is used for continuous output, while classification is employed
... Show MoreThis research aims to:
1 – Make a proposed module for (aesthetics) for the second stage - Department of Art Education under education theories.
2 - Verification from the effect of the proposed module on student achievement and motivation towards learning aesthetics material.
To verification the second goal we wording these two hypotheses:
1- There are no individual differences with statistically significant at level (0.05) between the student's scores average. (Experimental group ) who studied according to the proposed module and the average student's scores (control group) who studied in the usual way for the achievement test for the Aesthetics material.
2- There are no individual differences with statistically signifi