Biosignal analysis is one of the most important topics that researchers have tried to develop during the last century to understand numerous human diseases. Electroencephalograms (EEGs) are one of the techniques which provides an electrical representation of biosignals that reflect changes in the activity of the human brain. Monitoring the levels of anesthesia is a very important subject, which has been proposed to avoid both patient awareness caused by inadequate dosage of anesthetic drugs and excessive use of anesthesia during surgery. This article reviews the bases of these techniques and their development within the last decades and provides a synopsis of the relevant methodologies and algorithms that are used to analyze EEG signals. In addition, it aims to present some of the physiological background of the EEG signal, developments in EEG signal processing, and the effective methods used to remove various types of noise. This review will hopefully increase efforts to develop methods that use EEG signals for determining and classifying the depth of anesthesia with a high data rate to produce a flexible and reliable detection device.
AW Tarik, AW Ali T, A Salah, Journal of faculity of medicine Baghdad university, 2014 - Cited by 3
The objective that the researcher seeks to achieve through this research is to clarify the relationship between strategic management accounting techniques and the reliability of financial statements, and to measure the impact of these techniques as an independent variable with its three dimensions, which are: activities-based cost, target cost, and benchmarking on the reliability of financial statements as a dependent variable. To achieve this objective, the researcher did the following: First: Determine the research problem through the following question: Do strategic management accounting techniques affect the reliability of financial statements in industrial companies listed on the Palestine Exchange? Second: Making the analytical des
... Show MoreAn experiments were carried out at the College of Veterinary Medicine, University of Baghdad, during the period from October 26th 2023 to December 20th 2023, to study the effect of pasteurizing treatments of shell table egg using traditional Microwave oven on its quality characteristics during Zero, 1, 2, 4 and 8 weeks of refrigerator storage. A total of 120 fresh table eggs (White shell eggs) were collected from 20000 Luhman layer hens flock at Al-Amir project commercial farm, Al-Musaib city. These eggs were divided into 4 treatment of microwave pasteurization treatments which were Zero, 10, 20, and 30 sec. Results revealed that significant differences (P<0.05) for the internal characteristics of the egg after storage for 2, 4
... Show MoreExperiments were carried out at the College of Veterinary Medicine, University of Baghdad, during the period from October 26th 2023 to December 20th 2023, to study the effect of pasteurizing treatments of shell table egg using traditional Microwave oven on its quality characteristics during Zero, 1, 2, 4 and 8 weeks of refrigerator storage. A total of 120 fresh table eggs (White shell eggs) were collected from 20000 Luhman layer hens flock at Al-Amir project commercial farm, Al-Musaib city. These eggs were divided into 4 treatment of microwave pasteurization treatments which were Zero, 10, 20, and 30 sec. Results revealed that the numbers of total bacteria and total coliform on the surface of table egg shells is affected by pasteuri
... Show MoreThis study aims to suggest a technique for soil properties improvement of AL- Kadhimin shrine Minaret and to support the foundation, which has a tilt of roughly 80 cm from the vertical axis. The shrine of the AL- Kadhimin is made up of four minarets with two domes set in a large courtyard. The four minarets have skewed to varying degrees due to uncontrolled dewatering inside the shrine in recent years. However, the northeast minaret was the most inclined due to its proximity to the well placed inside shrine courtyard. When the well near the minaret is operated, the water level drops, increasing the effective stresses of the soil and causing differential settling of the minaret foundation. To maintain the minaret's foundation from potenti
... Show MoreHigh-resolution imaging of celestial bodies, especially the sun, is essential for understanding dynamic phenomena and surface details. However, the Earth's atmospheric turbulence distorts the incoming light wavefront, which poses a challenge for accurate solar imaging. Solar granulation, the formation of granules and intergranular lanes on the sun's surface, is important for studying solar activity. This paper investigates the impact of atmospheric turbulence-induced wavefront distortions on solar granule imaging and evaluates, both visually and statistically, the effectiveness of Zonal Adaptive Optics (AO) systems in correcting these distortions. Utilizing cellular automata for granulation modelling and Zonal AO correction methods,
... Show MoreDeep Learning Techniques For Skull Stripping of Brain MR Images
The popular art movement emerged in the mid-fifties in Britain in parallel with its appearance in America.. It was linked to contemporary social reality and what distinguishes this art is the most sophisticated and less aesthetic means and the most blatant in the field of media, ie back to the image used in the media, journalism, magazines, television and photo Which reflect the reality of the neutral artist. This research included the methodological framework represented by the research problem that emerged from pop art as a new experimental vision that emerged in the twentieth century and the importance of the research and its objectives and limits and the definition of terms. The theoretical framework dealt with evolution Technology,
... Show MoreCOVID 19 has spread rapidly around the world due to the lack of a suitable vaccine; therefore the early prediction of those infected with this virus is extremely important attempting to control it by quarantining the infected people and giving them possible medical attention to limit its spread. This work suggests a model for predicting the COVID 19 virus using feature selection techniques. The proposed model consists of three stages which include the preprocessing stage, the features selection stage, and the classification stage. This work uses a data set consists of 8571 records, with forty features for patients from different countries. Two feature selection techniques are used in