Cognitive radios have the potential to greatly improve spectral efficiency in wireless networks. Cognitive radios are considered lower priority or secondary users of spectrum allocated to a primary user. Their fundamental requirement is to avoid interference to potential primary users in their vicinity. Spectrum sensing has been identified as a key enabling functionality to ensure that cognitive radios would not interfere with primary users, by reliably detecting primary user signals. In addition, reliable sensing creates spectrum opportunities for capacity increase of cognitive networks. One of the key challenges in spectrum sensing is the robust detection of primary signals in highly negative signal-to-noise regimes (SNR).In this paper ,

Alzheimer's disease (AD) increasingly affects the elderly and is a major killer of those 65 and over. Different deep-learning methods are used for automatic diagnosis, yet they have some limitations. Deep Learning is one of the modern methods that were used to detect and classify a medical image because of the ability of deep Learning to extract the features of images automatically. However, there are still limitations to using deep learning to accurately classify medical images because extracting the fine edges of medical images is sometimes considered difficult, and some distortion in the images. Therefore, this research aims to develop A Computer-Aided Brain Diagnosis (CABD) system that can tell if a brain scan exhibits indications of

There is currently a significantly larger concentration of toxins in our environment than there was in the past. This is mostly attributable to the expansion of modern industry. This investigation was conducted in order to investigate various haematological and biochemical changes in order to determine the effects of Cd on the liver and kidney. Because of its long biological half-life, it is considered hazardous to human health. The effect of sub-lethal doses (40, 80 and 120 mg\Kg) of Cadmium (Cd) on male mice were evaluated for 4 weeks, and analysis was done to estimate their biochemical parameters and antioxidant enzymes. The results showed that Cd-treated mice had considerably lower packed cell volume, red blood cells, and haemoglobin. W

ABSTRACT Background: work-related musculoskeletal disorders represent an important occupational health issues among dentists especially neck and low back complaints. Biomarkers of tissue damage as results of occupational physical demands could be used for detection of work related musculoskeletal disorders. Aim: The aim of this study was to assess work- related musculoskeletal disorders, physical work load index, selected salivary biomarkers (Creatine kinase and C - reactive protein) and to find the relation among them. Subjects and Methods: Study participants are consisted of 112 dentists. They were selected from college of dentistry /Baghdad University, health care center in Bagdad city. They were of both gender and aged between 40-45 yea

The objective of this study is to evaluate the level of parathyroid hormone, Co enzyme Q and total antioxidant status in serum’s women with fibromyalgia syndrome firstly, then to demonstrate if these biochemical markers affected by age and obesity.

      This study was performed at Rheumatology and Rehabilitation Consultation Unit in Baghdad Teaching Hospital. Venous blood sample were drawn from (59) female with FMS and (30) control (without FMS). The serum was obtained after on standing in order to coagulate then centrifuged. The mean age± SD of FMS group was (42.22±15.34) years and for control was (40.7±18.22) years. Those participants were subdivided into four different groups acc

Database is characterized as an arrangement of data that is sorted out and disseminated in a way that allows the client to get to the data being put away in a simple and more helpful way. However, in the era of big-data the traditional methods of data analytics may not be able to manage and process the large amount of data. In order to develop an efficient way of handling big-data, this work studies the use of Map-Reduce technique to handle big-data distributed on the cloud. This approach was evaluated using Hadoop server and applied on EEG Big-data as a case study. The proposed approach showed clear enhancement for managing and processing the EEG Big-data with average of 50% reduction on response time. The obtained results provide EEG r

A condense study was done to compare between the ordinary estimators. In particular the maximum likelihood estimator and the robust estimator, to estimate the parameters of the mixed model of order one, namely ARMA(1,1) model.

Simulation study was done for a varieties the model.  using: small, moderate and large sample sizes, were some new results were obtained. MAPE was used as a statistical criterion for comparison.

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