Univesity of Thi-Qar Journal

This research deals with the study of binary logistic regression method for ‎classifying data for Covid-19 patients, Covid disease is one of the largest ‎health problem that swept the world at the present time, causing many ‎economic problems in the world, as the research aims to know the correct ‎classification of the influencing factors and to demonstrate the accuracy of ‎the method in the classification, as data for Covid-19 patients were used in ‎the Nasiriya General Hospital in Dhi Qar, several criteria were relied on, the ‎most important of which is the correct classification ratio of the ‎observations to indicate the performance and efficiency of the method used. ‎The Maximum Likelihood Estimation and Weighted Least Squares methods ‎were also used to estimate the parameters, the obtained results showed that ‎the logistic regression method performed well in the accuracy of the correct ‎classification of observation. ‎

The ratio of blood component and some special variable of Barbus sharpyie‏ ‏specimen has been measured during the hot months of summer, and the cold ‎months of winter extreme changes in ratio of Hb , P.C.V. , RBC , WBC and ‎the effort of blood component have been noticed, which proves ‎environmental and physiological fatigue undergone by this species of Iraqi ‎fish . Also, showed a clear effects between rising in temperatures and the ‎amounts of hemoglobin, P.C.V. , RBC , WBC .‎

The various hand EMG signal grasps are classified in this study. ‎Because EMG signals offer critical information about muscle activity, ‎they are commonly used as input to electro muscular control systems. ‎Each muscle performs a specific function in each movement. ‎Electromyography is a medical, healthcare, and human-machine ‎interaction diagnostic technique for acquiring an EMG signal (MMI). e ‎most important component of the locomotion system is the muscular ‎system. Accordingly, sensors were developed to detect the movement ‎system and diagnose the electromyogram. Nowadays, While ‎maintaining a modest size, it has improved and become more accurate. ‎In this paper, The EMG signals are converted into images using CWT, ‎then the EMG images features are extracted based on convolutional ‎neural network (CNN) , and finally, the EMG features are categorized ‎by an LS-SVM classifier in Matlab. The main objective of this study is ‎to classify grasps into six basic hand movements: (1) cylindrical, (2) ‎palm, (3) lat (4) sphere(5) Tip, and (6) Hook. Finally, ‎electrophysiological patterns of each movement were extracted by ‎extracting features from the images using CNN where EMG images are ‎divided into (70 percent ) training and (30 percent ) validation, and ‎then ‎these features are fed into classification using the least square support ‎vector machine. It produced an accuracy of 95.33%.‎

Gastrointestinal helminthes and protozoan parasites can cause ,acute and ‎chronic human infections , There is inadequate reliable studys on the ‎epidemiology of these parasites among patients attending al 'ahwar sector in ‎Thi- Qar province . This study was conducted using health centers data ‎obtained from al' ahwar Laboratories Unit.‎
‎ A total of 801 stool samples were recorded from January 2017-December ‎‎2017. Intestinal parasitic infections were recovered in 40.7% (326) of the ‎stool samples . The commonest pathogenic parasite was Entamoeba ‎histolytica . the prevalence of this protozoon 25.2%, then the nematode ‎Enterobius vermicularis, the prevalence of this helminthes was 10.9%. ‎finally the protozoon Giardia lamblia the prevalence was 4.6%.‎