COVID-19 is a disease that has abnormal over 170 nations worldwide. The number of infected people (either sick or dead) has been growing at a worrying ratio in virtually all the affected countries. Forecasting procedures can be instructed so helping in scheming well plans and in captivating creative conclusions. These procedures measure the conditions of the previous thus allowing well forecasts around the state to arise in the future. These predictions strength helps to make contradiction of likely pressures and significances. Forecasting procedures production a very main character in elastic precise predictions. In this case study used two models in order to diagnose optimal approach by compared the outputs. This study was introduced forecasting procedures into Artificial Neural Network models compared with regression model. Data collected from Al –Kindy Teaching Hospital from the period of 28/5/2019 to 28/7/2019 show an energetic part in forecasting. Forecasting of a disease can be done founded on several parameters such as the age, gender, number of daily infections, number of patient with other disease and number of death . Though, forecasting procedures arise with their private data of tests. This study chats these tests and also offers a set of commendations for the persons who are presently hostile the global COVID-19 disease.
The aim of the present study was to distinguish between healthy children and those with epilepsy by electroencephalography (EEG). Two biomarkers including Hurst exponents (H) and Tsallis entropy (TE) were used to investigate the background activity of EEG of 10 healthy children and 10 with epilepsy. EEG artifacts were removed using Savitzky-Golay (SG) filter. As it hypothesize, there was a significant changes in irregularity and complexity in epileptic EEG in comparison with healthy control subjects using t-test (p< 0.05). The increasing in complexity changes were observed in H and TE results of epileptic subjects make them suggested EEG biomarker associated with epilepsy and a reliable tool for detection and identification of this di
... Show MoreObesity among girls can lead to physical, psychological, or social problems. Enhancing self-esteem and reducing self-stigma toward obesity can play a crucial role in girls’ health. This study aims to assess girls’ self-esteem and its association with self-stigma toward obesity.
A descriptive cross-sectional design was used to meet the study’s objective. A convenience sampling method was used to gather the sample from 24 middle and high schools in five cities across Iraq from (January
This paper proposes a collaborative system called Recycle Rewarding System (RRS), and focuses on the aspect of using information communication technology (ICT) as a tool to promote greening. The idea behind RRS is to encourage recycling collectors by paying them for earning points. In doing so, both the industries and individuals reap the economical benefits of such system. Finally, and more importantly, the system intends to achieve a green environment for the Earth. This paper discusses the design and implementation of the RRS, involves: the architectural design, selection of components, and implementation issues. Five modules are used to construct the system, namely: database, data entry, points collecting and recording, points reward
... Show MoreAbstract The percent study aimed to determination the association between infant feeding practices and Insulin-Dependent Diabetes Mellitus (IDDM). The study was conducted at (he National Center of Diabetes in Baghdad City the Capital of Iraq throughout the period of January 2001 to January 2002. The sample was comprised of (200) mother of Insulin-Dependent Diabetes Mellitus (IDDM) of children under age of 12 years old. Data was collected through the use of a questionnaire that constructed by researcher and which were developed for the purpose of the present study. Reliability of the instruments was dete
In this paper, a new method of selection variables is presented to select some essential variables from large datasets. The new model is a modified version of the Elastic Net model. The modified Elastic Net variable selection model has been summarized in an algorithm. It is applied for Leukemia dataset that has 3051 variables (genes) and 72 samples. In reality, working with this kind of dataset is not accessible due to its large size. The modified model is compared to some standard variable selection methods. Perfect classification is achieved by applying the modified Elastic Net model because it has the best performance. All the calculations that have been done for this paper are in
The recent emergence of sophisticated Large Language Models (LLMs) such as GPT-4, Bard, and Bing has revolutionized the domain of scientific inquiry, particularly in the realm of large pre-trained vision-language models. This pivotal transformation is driving new frontiers in various fields, including image processing and digital media verification. In the heart of this evolution, our research focuses on the rapidly growing area of image authenticity verification, a field gaining immense relevance in the digital era. The study is specifically geared towards addressing the emerging challenge of distinguishing between authentic images and deep fakes – a task that has become critically important in a world increasingly reliant on digital med
... Show MoreGeomechanical modelling and simulation are introduced to accurately determine the combined effects of hydrocarbon production and changes in rock properties due to geomechanical effects. The reservoir geomechanical model is concerned with stress-related issues and rock failure in compression, shear, and tension induced by reservoir pore pressure changes due to reservoir depletion. In this paper, a rock mechanical model is constructed in geomechanical mode, and reservoir geomechanics simulations are run for a carbonate gas reservoir. The study begins with assessment of the data, construction of 1D rock mechanical models along the well trajectory, the generation of a 3D mechanical earth model, and runni
A new data for Fusion power density has been obtained for T-3He and T-T fusion reactions, power density is a substantial term in the researches related to the fusion energy generation and ignition calculations of magnetic confined systems. In the current work, thermal nuclear reactivities, power densities of a fusion reactors and the ignition condition inquiry are achieved by using a new and accurate formula of cross section, the maximum values of fusion power density for T-3He and TT reaction are 1.1×107 W/m3 at T=700 KeV and 4.7×106 W/m3 at T=500 KeV respectively, While Zeff suggested to be 1.44 for the two reactions. Bremsstrahlung radiation has also been determined to reaching self- sustaining reactors, Bremsstrahlung values are 4.5×
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