Epilepsy is a critical neurological disorder with critical influences on the way of living of its victims and prominent features such as persistent convulsion periods followed by unconsciousness. Electroencephalogram (EEG) is one of the commonly used devices for seizure recognition and epilepsy detection. Recognition of convulsions using EEG waves takes a relatively long time because it is conducted physically by epileptologists. The EEG signals are analyzed and categorized, after being captured, into two types, which are normal or abnormal (indicating an epileptic seizure).  This study relies on EEG signals which are provided by Arrhythmia Database. Thus, this work is a step beyond the traditional database mission of delivering use

Aerial manipulation of objects has a number of advantages as it is not limited by the morphology of the terrain. One of the main problems of the aerial payload process is the lack of real-time prediction of the interaction between the gripper of the aerial robot and the payload. This paper introduces a digital twin (DT) approach based on impedance control of the aerial payload transmission process. The impedance control technique is implemented to develop the target impedance based on emerging the mass of the payload and the model of the gripper fingers. Tracking the position of the interactional point between the fingers of gripper and payload, inside the impedance control, is achieved using model predictive control (MPD) approach.

Let G be a graph with p vertices and q edges and  be an injective function, where k is a positive integer. If the induced edge labeling   defined by for each is a bijection, then the labeling f is called an odd Fibonacci edge irregular labeling of G. A graph which admits an odd Fibonacci edge irregular labeling is called an odd Fibonacci edge irregular graph. The odd Fibonacci edge irregularity strength ofes(G) is the minimum k for which G admits an odd Fibonacci edge irregular labeling. In this paper, the odd Fibonacci edge irregularity strength for some subdivision graphs and graphs obtained from vertex identification is determined.

       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

Background: Diabetes is a chronic illness that requires continuing medical care to prevent acute complications and to reduce the risk of long-term complication. Eye
diseases are the most feared complication of diabetes. The main disorders include diabetic retinopathy, cataracts and glaucoma. Early detection of these conditions is
important to avoid risk of vision affection or even blindness.
Objectives: This study aimed to assess the prevalence and risk factors for eye problems among 20-65 years old diabetics' patients.
Methods: We studied 2540 diabetic patients selected from the Specialized Center for Endocrinology & Diabetes and the National Center for Treatment & Research of
Diabetes in Al-Mu

Mass transfer correlations for iron rotating cylinder electrode in chloride/sulphate solution, under isothermal and
controlled heat transfer conditions, were derived. Limiting current density values for the oxygen reduction reaction from
potentiostatic experiments at different bulk temperatures and various turbulent flow rates, under isothermal and heat
transfer conditions, were used for such derivation. The corelations were analogous to that obtained by Eisenberg et all
and other workers.

Among the undesirable effects of soil compaction is a measurable reduction in plant growth and crop yield. The prevailing belief is that compacted tillage pans are caused by repetitive farming practices, heavy tractors, tillage tools, and field traffic. This experiment was conducted to determine and map the hardpan layers across an agricultural field through advanced technologies of precision agriculture. These valuable techniques such as data logger, yield map, and data analysis of performance indicators were linked with accurate global positioning systems (GPS) datasets. These important technologies provided the farmers and helped them to identify and manage areas of the fields with higher compacted layers. Three ground speeds 4.3

The expanding of the medically important diseases created by multidrug-resistant Acinetobacter baumannii warrants the evolve a new methodology for prevention includes vaccination and treatment. Totally of forty-five clinical isolates identified as A.baumannii were obtained from hospitalized patients from three hospital in Baghdad City during the period from February 2016 to August 2016. Followed by diagnosing using different methods. Every strain was tested for susceptibility testing also some important virulence factorswere detected. Two isolates were chosen for the immunization and vaccine model, the first one remittent for most antibiotics except one are too virulence (strong) and the second is less virulent and resistance (weak).Enzyme-

Particulate matter (PM) emitted from diesel engine exhaust have been measured in terms of mass, using
99.98 % pure ethanol blended directly, without additives, with conventional diesel fuel (gas – oil),to
get 10 % , 15 %, 20 % ethanol emulsions . The resulting PM collected has been compared with those
from straight diesel. The engine used is a stationary single cylinder, variable compression ratio Ricardo
E6/US. This engine is fully instrumented and could run as a compression or spark ignition.
Observations showed that particulate matter (PM) emissions decrease with increasing oxygenate
content in the fuel, with some increase of fuel consumption, which is due to the lower heating value of
ethanol. The reduction in

In this study, a mathematical model is presented to study the chemisorption of two interacting atoms on solid surface in the presence of laser field. Our mathematical model is based on the occupation numbers formula that depends on the laser field which we derived according to Anderson model for single atom adsorbed on solid surface. Occupation numbers formula and chemisorption energy formula are derived for two interacting atoms (as a diatomic molecule) as they approach to the surface taking into account the correlation effects on each atom and between atoms. This model is characterized by obvious dependence of all relations on the system variables and the laser field characteristics which gives precise description for the molecule –