The growth of developments in machine learning, the image processing methods along with availability of the medical imaging data are taking a big increase in the utilization of machine learning strategies in the medical area. The utilization of neural networks, mainly, in recent days, the convolutional neural networks (CNN), have powerful descriptors for computer added diagnosis systems. Even so, there are several issues when work with medical images in which many of medical images possess a low-quality noise-to-signal (NSR) ratio compared to scenes obtained with a digital camera, that generally qualified a confusingly low spatial resolution and tends to make the contrast between different tissues of body are very low and it difficult to co

Hydatidosis is a zoonotic, helminthes parasitic disease that cause veterinary and human problems due to economic burden. Amis of the current study was to estimate the prevalence rate of hydatidosis infecting different organs of sheep slaughtered in street. In addition, investigate the relationship between age, gender and the infected rates in some Baghdad areas during a period from may to end of July 2018.A total of 188 sheep was examined for detection of Hydatid cyst in different organs using macroscopic and microscopic examination The overall prevalence rate of 47.9% was recorded. The results indicate non significant differences according to age and gender, the highest rate 57% was observed in sheep more than one year old compare

Opportunistic fungal infections due to the immune- compromised status of renal transplant patients are related to high rates of morbidity and mortality regardless of their minor incidence. Delayed in identification of invasive fungal infections (IFIs), will lead to delayed treatment and results in high mortality in those populations. The study aimed to assess the frequency of invasive fungal infection in kidney transplant recipients by conventional and molecular methods. This study included 100 kidney transplant recipients (KTR) (75 males, and 25 females), collected from the Centre of Kidney Diseases and Transplantation in the Medical City of Baghdad. Blood samples were collected during the period from June 2018 to April 2019. Twent

Context and its influence in direction of reference by Abi Hussein Al Basri

This study discussed a biased estimator of the Negative Binomial Regression model known as (Liu Estimator), This estimate was used to reduce variance and overcome the problem Multicollinearity between explanatory variables, Some estimates were used such as Ridge Regression and Maximum Likelihood Estimators, This research aims at the theoretical comparisons between the new estimator (Liu Estimator) and the estimators

In this work, spinel ferrites (NiCoFe₂O₄) were prepared as thin films by dc reactive dual-magnetron co-sputtering technique. Effects of some operation parameters, such as inter-electrode distance, and preparation conditions such as mixing ratio of argon and oxygen in the gas mixture, on the structural and spectroscopic characteristics of the prepared samples were studied. For samples prepared at inter-electrode distance of 5 cm, only one functional group of OH^- was observed in the FTIR spectra as all bands belonging to the metal-oxygen vibration were observed. Similarly, the XRD results showed that decreasing the pressure of oxygen in the gas mixture lead to grow more crystal planes in the samples prepare

To perform a secure evaluation of Indoor Design data, the research introduces a Cyber-Neutrosophic Model, which utilizes AES-256 encryption, Role-Based Access Control, and real-time anomaly detection. It measures the percentage of unpredictability, insecurity, and variance present within model features. Also, it provides reliable data security. Similar features have been identified between the final results of the study, corresponding to the Cyber-Neutrosophic Model analysis, and the cybersecurity layer helped mitigate attacks. It is worth noting that Anomaly Detection successfully achieved response times of less than 2.5 seconds, demonstrating that the model can maintain its integrity while providing privacy. Using neutrosophic sim

In data mining, classification is a form of data analysis that can be used to extract models describing important data classes. Two of the well known algorithms used in data mining classification are Backpropagation Neural Network (BNN) and Naïve Bayesian (NB). This paper investigates the performance of these two classification methods using the Car Evaluation dataset. Two models were built for both algorithms and the results were compared. Our experimental results indicated that the BNN classifier yield higher accuracy as compared to the NB classifier but it is less efficient because it is time-consuming and difficult to analyze due to its black-box implementation.

Pollen grains morphology have been studied for the wild species of the genus Erysimum L. which belong to Crucifereae family in Iraq. These species are E. filifolium Boiss. et Hausskn., E. oleifolium J. Gay, E. repandum L., E. eginense Hausskn. ex Bornm., E. aucheranum J. Gay, E. cheiranthoides L., E. alpestre Ky. ex Boiss., E. kurdicum Boiss. et Hausskn., E. tenellum DC., E. strophades Boiss., E. gladiiferum Boiss. et Hausskn., E. nasturtioides Boiss. et Hausskn. The study was performe by using light microscope . The study reveal that there was only one type of pollen grain named Tricoplate in all studied species . The study also demonstrated that there were differences among pollen grains morphology . The species E. kurdicum , E. alpestre