The issue of image captioning, which comprises automatic text generation to understand an image’s visual information, has become feasible with the developments in object recognition and image classification. Deep learning has received much interest from the scientific community and can be very useful in real-world applications. The proposed image captioning approach involves the use of Convolution Neural Network (CNN) pre-trained models combined with Long Short Term Memory (LSTM) to generate image captions. The process includes two stages. The first stage entails training the CNN-LSTM models using baseline hyper-parameters and the second stage encompasses training CNN-LSTM models by optimizing and adjusting the hyper-parameters of

RM Abbas, AA Abdulhameed, AI Salahaldin, International Conference on Geotechnical Engineering, 2010

n this work, the effect of gamma rays on blood thinning drugs was studied using the drug (Aspirin), where gamma rays were spread with the drug using a radioactive source (Co60), and 15,000 grams of Aspirin were placed in the device (gamma chamber 900). The drug was subjected to different irradiation doses (5 KGy, 10 KGy, 15 KGy) and the amount of absorption of the drug was observed in the gamma for different doses and the study of x-rays. After confirming the absorption of the drug to radiation, the effect of the drug on blood thinning was calculated using the rat model and compared with the same drug and the same dose but without exposing the drug to radiation and comparing all results with the control group. The way drugs absorbed radiati