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

Image compression plays an important role in reducing the size and storage of data while increasing the speed of its transmission through the Internet significantly. Image compression is an important research topic for several decades and recently, with the great successes achieved by deep learning in many areas of image processing, especially image compression, and its use is increasing Gradually in the field of image compression. The deep learning neural network has also achieved great success in the field of processing and compressing various images of different sizes. In this paper, we present a structure for image compression based on the use of a Convolutional AutoEncoder (CAE) for deep learning, inspired by the diversity of human eye

In the latest years there has been a profound evolution in computer science and technology, which incorporated several fields. Under this evolution, Content Base Image Retrieval (CBIR) is among the image processing field. There are several image retrieval methods that can easily extract feature as a result of the image retrieval methods’ progresses. To the researchers, finding resourceful image retrieval devices has therefore become an extensive area of concern. Image retrieval technique refers to a system used to search and retrieve images from digital images’ huge database. In this paper, the author focuses on recommendation of a fresh method for retrieving image. For multi presentation of image in Convolutional Neural Network (CNN),

Aim: The study aimed to investigate the presence of the specific B1 gene T gondii in blood and milk samples from natural infected cattle and pregnant women (16-30 weeks) whose examination performed by the officers at the women's and children's Educational hospital in Al-Diwaniyah, Iraq. Materials and methods: A total of 150 serum samplings were collected analysed and scanned for Anti-T gondi antibodies (75 naturally-infected goats and 75 pregnant women with Toxoplasma). Polymerase chain reaction (PCR) was used to detect of B1(399pb) gene in 26 goat's blood samples and 7 samples from pregnant women. Results: A quick-test anti-cassette gondii results showed 26 positive samples of goats in a percentage of 34,666 percent, while a higher percent

   The most frequently diagnosed condition in women at the age of reproduction is the polycystic ovarian syndrome (PCOS).it could be related to a complex endocrine condition, due to its heterogeneity and uncertainty about its etiology, as the clinical highlights of PCOS incorporate those related to reproductive signs such as decreased frequency of ovulation, irregular menstrual cycles, decreased fertility. Carnitine plays a substantial role in weight loss, glucose tolerance, insulin function and fatty acid metabolism. Thus carnitine plays a crucial role in controlling  obesity, insulin resistance, oxidative stress that are  associated with PCOS .While, AGEs are a diverse group of reactive molecules that are formed end

Background: Coping skills play a vital role in managing the physical and psychological effects of breast cancer (BC). Despite improvements in early detection and treatment, Breast cancer survivors continue to face long-term challenges after diagnosis. Therefore, this study aims to evaluate the coping skills employed by breast cancer women in Iraq and to identify the sociodemographic, clinical, and psychological factors associated with these coping skills. Methods: A cross-sectional study was conducted among 244 breast cancer women in The Medical City Teaching Oncology Hospital, Baghdad, Iraq, from August 2023 to October 2023, coping skills and psychological factors were assessed using the BRIEF COPE-28, and Hospital Anxiety Depression scale

One-hundred and twenty Iraqi women (60 single women and 60 married women) with age ranges from (17-49) years have been involved in this study to estimate the levels of anti-mullerian hormone (AMH) and follicle stimulating hormone (FSH) as markers of ovarian aging. The descriptive data [age, body mass index (BMI), age at menarche, duration of menarche] have been recorded. Blood samples were collected from the studied women to determine the levels of AMH and FSH. The results revealed non-significant (p>0.05) differences in levels of AMH and FSH between single women and married women. A significant negative correlation was observed between AMH levels and age in single women (r=-0.519, p<0.05) and married women (r=-0.433, p<0.05). A no