In the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial lung CT-scans into two groups (COVID-19 and NonCOVID-19) had been proposed. A dataset used is 960 slices of CT scan collected from Iraqi patients /Ibn Al-Nafis teaching hospital. The performance metrics are used in this study (accuracy, recall, precision, and F1 scores). The results indicate that the proposed approach generated a high-quality model for the collected dataset, with an overall accuracy of 98.95% and an overall recall of 97 %.
Recently, wireless charging based RF harvesting has interfered our lives [1] significantly through the different applications including biomedical, military, IoT, RF energy harvesting, IT-care, and RFID technologies. Wirelessly powered low energy devices become significantly essential for a wide spectrum of sensing applications [1]. Such devices require for low energy resources from sunlight, mechanical vibration, thermal gradients, convection flows or other forms of harvestable energy [2]. One of the emerging power extraction resources based on passive devices is harvesting radio frequency (RF) signals powers [3]–[5]. Such applications need devices that can be organized in very large numbers, so, making separate node battery impractical.
... Show MoreThe evaluation of banks plays an important role in maintaining the interests of customers with the bank as well as providing continuous supervision and control by the Central Bank. The Central Bank of Iraq conducted an assessment of the Iraqi banks through the implementation of the CAMEL model during a certain period. This evaluation did not continue. The research provides continuity to the Central Bank's assessment and as a step to continue the evaluation process for all banks through the use of the CAMEL model. ROA and ROE by using the regression model for four Iraqi banks registered in the Iraqi market for securities during the period 2010-2016. The results showed that the capital and profitability indicators have a significan
... Show MoreDeep 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
... Show MoreThe problem of divorce from the phenomena that characterized the nature of privacy,
although their impact beyond the individual to include the community as a whole, the parties
to the relationship affected by divorce caused them harm moral and material for a long time,
resulting imbalance in the personal relationship and family and social relations because of the
high divorce rates, particularly in Iraq high rates of 28690 thousand cases in 2004 to 59 515
thousand cases in 2011 and an increase of more than (100%) during the period above, and this
rise caused by aggravation of many of the problems led the reasons for social, economic and
incompatibility spouses, health and lack of reproduction, not spending The wife a
It is considered as one of the statistical methods used to describe and estimate the relationship between randomness (Y) and explanatory variables (X). The second is the homogeneity of the variance, in which the dependent variable is a binary response takes two values (One when a specific event occurred and zero when that event did not happen) such as (injured and uninjured, married and unmarried) and that a large number of explanatory variables led to the emergence of the problem of linear multiplicity that makes the estimates inaccurate, and the method of greatest possibility and the method of declination of the letter was used in estimating A double-response logistic regression model by adopting the Jackna
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It is considered as one of the statistical methods used to describe and estimate the relationship between randomness (Y) and explanatory variables (X). The second is the homogeneity of the variance, in which the dependent variable is a binary response takes two values (One when a specific event occurred and zero when that event did not happen) such as (injured and uninjured, married and unmarried) and that a large number of explanatory variables led to the emergence of the problem of linear multiplicity that makes the estimates inaccurate, and the method of greatest possibility and the method of declination of the letter was used in estimating A double-response logistic regression model by adopting the Jackna
... Show MoreSeeds, beans, leaves, fruit peel and seeds of five plants (Ferula assa-foetida, Coffea robusta, Olea europaea, Punica granatum and Vitis vinifera, respectively) were extracted with four solvents (distilled water, 80% methanol, 80% acetone and a mixed solvent that included methanol, ethanol, acetone and n-butanol at proportions 7:1:1:1). Such manipulation yielded 20 extracts, which were phytochemically analyzed for total polyphenols (TP) and flavonoids (TF). The DPPH (2,2-diphenyl-1-picrylhydrazyl) radical scavenging activity (RSA) and DPP-4 (dipeptidyl peptidase-4) relative inhibition activity (RIA) were also assessed for each extract. The results revealed that mixed solvent extract of V.
... Show MoreThe efficiency of Nd:YAG laser radiation in removing debris and smear layer from prepared root
canal walls was studied. Fifty-seven human extracted single rooted anterior teeth were divided into three
groups. A group that was not lased is considered as a control group. The remaining teeth were exposed to
different laser parameters regarding laser energy, repetition rate and exposure time. For the case of the set of
parameters of 7 mJ laser energy, the cleaning was maximum at 3 p.p.s. repetition rate for 3 seconds exposure
time for, the coronal, middle and apical thirds. Above and below this energy level, there was an overdose
(melting) or under dose (no effect). Nevertheless for 10mJ laser energy case, the cleaning effi
In this research, a low cost, portable, disposable, environment friendly and an easy to use lab-on-paper platform sensor was made. The sensor was constructed using a mixture of Rhodamine-6G and gold nanoparticles also Sodium chloride salt. Drop–casting method was utilized as a technique to make a platform which is a commercial office paper. A substrate was characterized using Field Emission Scanning Electron Microscope, Fourier transform infrared spectroscopy, UV-visible spectrophotometer and Raman Spectrometer. Rh-6G Raman signal was enhanced based on Surface Enhanced Raman Spectroscopy technique utilized gold nanoparticles. High Enhancement factor of Plasmonic commercial office paper reaches up to 0.9 x105 because of local surface pl
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