The hydrological process has a dynamic nature characterised by randomness and complex phenomena. The application of machine learning (ML) models in forecasting river flow has grown rapidly. This is owing to their capacity to simulate the complex phenomena associated with hydrological and environmental processes. Four different ML models were developed for river flow forecasting located in semiarid region, Iraq. The effectiveness of data division influence on the ML models process was investigated. Three data division modeling scenarios were inspected including 70%–30%, 80%–20, and 90%–10%. Several statistical indicators are computed to verify the performance of the models. The results revealed the potential of the hybridized s

The ability of the human brain to communicate with its environment has become a reality through the use of a Brain-Computer Interface (BCI)-based mechanism. Electroencephalography (EEG) has gained popularity as a non-invasive way of brain connection. Traditionally, the devices were used in clinical settings to detect various brain diseases. However, as technology advances, companies such as Emotiv and NeuroSky are developing low-cost, easily portable EEG-based consumer-grade devices that can be used in various application domains such as gaming, education. This article discusses the parts in which the EEG has been applied and how it has proven beneficial for those with severe motor disorders, rehabilitation, and as a form of communi

The investigation of machine learning techniques for addressing missing well-log data has garnered considerable interest recently, especially as the oil and gas sector pursues novel approaches to improve data interpretation and reservoir characterization. Conversely, for wells that have been in operation for several years, conventional measurement techniques frequently encounter challenges related to availability, including the lack of well-log data, cost considerations, and precision issues. This study's objective is to enhance reservoir characterization by automating well-log creation using machine-learning techniques. Among the methods are multi-resolution graph-based clustering and the similarity threshold method. By using cutti

   The emerge of capitalism beside appearing modern and contemporary political systems which had become hold out it is semi-domination on more vital space of human community life, it is through some vital apparatus, which the free market apparatus had make important one which depend on achieve the privileges of the capitalism elite whom standing on it, especially the finance elite. Thus the achievement of the profit had become the main podcasted of those elite which whom the really advancer of the Globalization system, this is which incarnated by the appears and extend of the (COVID-19) fatality pandemic in the end of last year, whereas reveals widespread of it in more than one states in the world, especially the developed coun

Due to its safety, low cost, real-time nature, and widespread availability, ultrasound has been employed as a diagnostic technique for numerous intraocular disorders. Unfortunately, speckle artifact that depends on the tissue is seen in ultrasound imaging. In this study, we present a technique for lowering speckle noise and enhancing ultrasound images to enhance human diagnostic performance. This technique combines the undecimated wavelet transform (UDWT) with a wavelet coefficient mapping function, which was utilized to improve the contrast of the denoised images acquired from the first component after the noise was removed using the UDWT. This technique can be used to enhance the visual quality of medical photographs as well as to enha

Early detection of brain tumors is critical for enhancing treatment options and extending patient survival. Magnetic resonance imaging (MRI) scanning gives more detailed information, such as greater contrast and clarity than any other scanning method. Manually dividing brain tumors from many MRI images collected in clinical practice for cancer diagnosis is a tough and time-consuming task. Tumors and MRI scans of the brain can be discovered using algorithms and machine learning technologies, making the process easier for doctors because MRI images can appear healthy when the person may have a tumor or be malignant. Recently, deep learning techniques based on deep convolutional neural networks have been used to analyze med

Abstract

This study aims to identify the repercussions of the Corona pandemic (Covid 19) and its impact on the educational and psychological functions of the Omani family from the point of view of a number of fathers and mothers. Drive for a group of fathers and mothers, some of whom work in the government sector and others are mothers enrolled in graduate studies programs at the university, their ages range between (30-50 years) totally (28) mothers and fathers: 22 mothers and 6 fathers. The results showed that the repercussions of the transformation of e-learning, home quarantine, social distancing, and the challenges associated with them were among the most frequent responses that posed a real challenge to the

Coronavirus disease 2019 (COVID-19) is a flu-like infection caused by a novel virus known as Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2). After the widespread around the world, it was announced by the World Health Organization (WHO) as a global pandemic. The symptoms of COVID-19 may arise within 2 weeks and the severity ranged from mild with signs of respiratory infection to severe cases of organ failure and even death. Management of COVID-19 patients includes supportive treatment and pharmacological medications expected to be effective with no definitive cure of the disease. The aims of this study are highlighting the management protocol and supportive therapy especially vitamin D and manifesting the clinical symptoms b

Susceptibility to the pandemic coronavirus disease 2019 (COVID-19) has recently been associated with ABO blood groups in patients of different ethnicities. This study sought to understand the genetic association of this polymorphic system with risk of disease in Iraqi patients. Two outcomes of COVID-19, recovery and death, were also explored. ABO blood groups were determined in 300 hospitalized COVID-19 Iraqi patients (159 under therapy, 104 recovered, and 37 deceased) and 595 healthy blood donors. The detection kit for 2019 novel coronavirus (2019-nCoV) RNA (PCR-Fluorescence Probing) was used in the diagnosis of disease.