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

Aim: To evaluate the commercial pure titanium disks that structuring by laser in two design (dot and groove) each one with three different laser scan (5, 15 and 25) and comparing with titanium surface that not subjected to any surface structuring (control) through measuring the wettability test and surface roughness test. Materials and methods: Structuring on the surface of the commercial pure titanium (CP Ti) disks was performed via using fiber laser CNC machine in two design (dot and groove) in three different laser scans (5, 15 and 25), then the structuring disks analyzed with the control group by atomic force microscope and water contact angle test. Results: The results of this study showed that the surface roughness and the wettability

The adoption of many mathematical concepts contributes to the construction of models of sports and the population can be interpreted to explain the movement and growth of the population lead to proper planning to manage the requirements of the population and meet their needs of providing education or providing medical services, health and others. In this study, the number of births in the Governorate of Basrah for the period (1998-2050) is estimated to be based on the assumption that the population of the visually impaired is a stable society. If the rate of growth is (0.0492), some demographic indicators are important for maintaining the average age of women at pregnancy (27.817). Each woman will give birth (3.74) female birth d

     Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod

The aim of this study was to isolate and identify the cyanobacterium Scytonema hofmanni Var. calcicolum from the domestic drinking tanks as a new record in Iraqi drinking water. Scytonema hofmanni var. calcicolum, a filamentous freshwater cyanobacterium (blue-green alga). This alga was isolated from the walls of the domestic plastic water tanks in Al- karkh/ Baghdad city on July 2014. The sampling was performed by collecting three samples from this tanks, the three examined samples microscopically revealed the dominance of this cyanobacterium as unialgal in the studied samples. The results showed this alga has the ability to tolerate high temperature up to 42 Cº and very low light intensity inside the tanks which up to 10 μE/m²/s.

Diyala river is the most important tributaries in Iraq, this river suffering from pollution, therefore, this research aimed to predict organic pollutants that represented by biological oxygen demand BOD, and inorganic pollutants that represented by total dissolved solids TDS for Diyala river in Iraq, the data used in this research were collected for the period from 2011-2016 for the last station in the river known as D17, before the river meeting Tigris river in Baghdad city. Analysis Neural Network ANN was used in order to find the mathematical models, the parameters used to predict BOD were seven parameters EC, Alk, Cl, K, TH, NO3, DO, after removing the less importance parameters. While the parameters that used to predict TDS were fourte

The research took the spatial autoregressive model: SAR and spatial error model: SEM  in an attempt to provide practical evidence that proves the importance of spatial analysis, with a particular focus on the importance of using regression models spatial and that includes all of the spatial dependence, which we can test its presence or not by using Moran test. While ignoring this dependency may lead to the loss of important information about the phenomenon under research is reflected in the end on the strength of the statistical estimation power, as these models are the link between the usual regression models with time-series models. The spatial analysis had been applied to Iraq Household Socio-Economic Survey: IHS

The subject of dumping is considering today one of the subjects in which form an obstruction arise in front of the cycle of growth for some countries , such as the study of dumping is capturing a large attention by the competent because either a big  role and effect in growing the economies of nations then the subject of dumping became a field turn around its sides many measures and laws … and may be done resorting to by many states of the world to anti-dumping as approach of determent weapon delimit  the impact of dumping and gives the national agriculture sector the opportunity for rising and growing so this section of international economics is capturing a special importance and represent in same time an important