IA Ali, FK Emran, DF Salloom, Annals of the Romanian Society for Cell Biology, 2021

In present work the effort has been put in finding the most suitable color model for the application of information hiding in color images. We test the most commonly used color models; RGB, YIQ, YUV, YCbCr1 and YCbCr2. The same procedures of embedding, detection and evaluation were applied to find which color model is most appropriate for information hiding. The new in this work, we take into consideration the value of errors that generated during transformations among color models. The results show YUV and YIQ color models are the best for information hiding in color images.

Monaural source separation is a challenging issue due to the fact that there is only a single channel available; however, there is an unlimited range of possible solutions. In this paper, a monaural source separation model based hybrid deep learning model, which consists of convolution neural network (CNN), dense neural network (DNN) and recurrent neural network (RNN), will be presented. A trial and error method will be used to optimize the number of layers in the proposed model. Moreover, the effects of the learning rate, optimization algorithms, and the number of epochs on the separation performance will be explored. Our model was evaluated using the MIR-1K dataset for singing voice separation. Moreover, the proposed approach achi

The Mauddud reservoir, Khabaz oil field which is considered one of the main carbonate reservoirs in the north of Iraq. Recognizing carbonate reservoirs represents challenges to engineers because reservoirs almost tend to be tight and overall heterogeneous. The current study concerns with geological modeling of the reservoir is an oil-bearing with the original gas cap. The geological model is establishing for the reservoir by identifying the facies and evaluating the petrophysical properties of this complex reservoir, and calculate the amount of hydrocarbon. When completed the processing of data by IP interactive petrophysics software, and the permeability of a reservoir was calculated using the concept of hydraulic units then, there

Machine learning models have recently provided great promise in diagnosis of several ophthalmic disorders, including keratoconus (KCN). Keratoconus, a noninflammatory ectatic corneal disorder characterized by progressive cornea thinning, is challenging to detect as signs may be subtle. Several machine learning models have been proposed to detect KCN, however most of the models are supervised and thus require large well-annotated data. This paper proposes a new unsupervised model to detect KCN, based on adapted flower pollination algorithm (FPA) and the k-means algorithm. We will evaluate the proposed models using corneal data collected from 5430 eyes at different stages of KCN severity (1520 healthy, 331 KCN1, 1319 KCN2, 1699 KCN3 a

Keys for 22 species representing ten genera Thripidae collection carried out during 1999-2001 in different localities in the middle of Iraq. Of them four species are described as new to science, Frankliniella megacephala sp. nov; Retithrips bagdadensis sp. nov; Chirothrips imperatus sp. nov; Taeniothrips tigridis sp. nov; Another thirteen species are recorded for the first time in Iraq; Thrips meridionalis (Pri.); Microcephalothrips abdominils (Crawford); Scolothrips pallidus (Beach); Scritothrips mangiferae Pri.; Frankliniella tritici Bagnall; Frankliniella schultzie Trybom; Frankliniella unicolor Morgan; Retithrips aegypticus Mar

The importance of this research is to clarify the nature and the relationship between the indicators of financial policy and banking stability in Iraq, as well as to find a composite index reflects the state of banking stability in Iraq in order to provide an appropriate means to help policymakers in making appropriate decisions before the occurrence of financial crises.

     Hence, the problem of research is that the fiscal policy has implications for the macro economy and does not rule out its impact on banking stability. Moreover, the central bank does not possess a single indicator that reflects the stability of the banking system, rather than the scattered indicators that depend o

In subterranean coal seam gas (CSG) reservoirs, massive amounts of small-sized coal fines are released during the production and development stages, especially during hydraulic fracturing stimulation. These coal fines inevitably cause mechanical pump failure and permeability damage due to aggregation and subsequent pore-throat blockage. This aggregation behavior is thus of key importance in CSG production and needs to be minimized. Consequently, such coal fines dispersions need to be stabilized, which can be achieved by the formulation of improved fracturing fluids. Here, we thus systematically investigated the effectiveness of two additives (ethanol, 0.5 wt % and SDBS, 0.001 and 0.01 wt %) on dispersion stability for a wide range of condit