Emotion could be expressed through unimodal social behaviour’s or bimodal or it could be expressed through multimodal. This survey describes the background of facial emotion recognition and surveys the emotion recognition using visual modality. Some publicly available datasets are covered for performance evaluation. A summary of some of the research efforts to classify emotion using visual modality for the last five years from 2013 to 2018 is given in a tabular form.
The aim of this study was to Identifying The Effect of using Linear programming and Branching programming by computer in Learning and Retention of movement concatenation(Linkwork) in parallel bars in Artistic Gymnastics. The searchers have used the experimental method. The search subject of this article has been taken (30) male - students in the second class from the College of Physical Education/University of Baghdad divided into three groups; the first group applied linear programming by computer, and the second group has been applicated branching programming by computer, while precision group used traditional method in the college. The researchers concluded the results by using the statistical bag for social sciences (spss) such as both
... Show MoreBackground: Data on SARS-CoV-2 from developing countries is not entirely accurate, demanding incorporating digital epidemiology data on the pandemic.
Objectives: To reconcile non-Bayesian models and artificial intelligence connected with digital and classical (non-digital) epidemiological data on SARS-CoV-2 pandemic in Iraq.
Results: Baghdad and Sulaymaniyah represented statistical outliers in connection with daily cases and recoveries, and daily deaths, respectively. Multivariate tests and neural networks detected a predictor effect of deaths, recoveries, and daily cases on web searches concerning two search terms, "كورونا" and "Coronavirus" (Pillai's Trace val
Coronavirus disease (COVID-19), which is caused by SARS-CoV-2, has been announced as a global pandemic by the World Health Organization (WHO), which results in the collapsing of the healthcare systems in several countries around the globe. Machine learning (ML) methods are one of the most utilized approaches in artificial intelligence (AI) to classify COVID-19 images. However, there are many machine-learning methods used to classify COVID-19. The question is: which machine learning method is best over multi-criteria evaluation? Therefore, this research presents benchmarking of COVID-19 machine learning methods, which is recognized as a multi-criteria decision-making (MCDM) problem. In the recent century, the trend of developing
... Show MoreBackground: Colorectal cancer (CRC) represents the second most common malignancy and the fourth most common cause of cancer deaths. CRC can manifest early with bright red bleeding per rectum, tenesmus, and altered bowel habits. These symptoms are often attributed to benign lesions, including anal fissure. Our objective is to highlight the alarming scenario of an anal fissure masking the clinical features of an underlying colorectal cancer in healthy middle-aged patients.
Case Report
Our case report aims to discuss how congruent clinical features of benign-looking anal fissure can delay the diagnosis of rectal cancer. In January 2019, a healthy forty-four years old Iraqi male with no famil
... Show MoreThe utilization of artificial intelligence techniques has garnered significant interest in recent research due to their pivotal role in enhancing the quality of educational offerings. This study investigated the impact of employing artificial intelligence techniques on improving the quality of educational services, as perceived by students enrolled in the College of Pharmacy at the University of Baghdad. The study sample comprised 379 male and female students. A descriptive-analytical approach was used, with a questionnaire as the primary tool for data collection. The findings indicated that the application of artificial intelligence methods was highly effective, and the educational services provided to students were of exceptional quality.
... Show MoreAbstract
As one year elapsed since COVID-19 outbreak, venous and arterial thromboses are increasingly reported in different vascular territories. Once accessed by the virus, the endothelial cells, abundant in angiotensin converting enzyme-2 (ACE-2) protein, will be activated by the inflammatory process leading to coagulopathy and vascular lesions. Herein, we describe a case of extensive thrombosis of the infra-renal inferior vena cava and iliac femoral vein in a man of 62 and a case of acute superficial femoral artery thrombosis in a lady of 55. Both were COVID-19 confirmed cases with severe pneumonia, high D-Dimer levels and risk factors for severe disease or death. Despite presentation 1-2 weeks after the onse
... Show MoreOver the years, the prediction of penetration rate (ROP) has played a key rule for drilling engineers due it is effect on the optimization of various parameters that related to substantial cost saving. Many researchers have continually worked to optimize penetration rate. A major issue with most published studies is that there is no simple model currently available to guarantee the ROP prediction.
The main objective of this study is to further improve ROP prediction using two predictive methods, multiple regression analysis (MRA) and artificial neural networks (ANNs). A field case in SE Iraq was conducted to predict the ROP from a large number of parame
Drilling deviated wells is a frequently used approach in the oil and gas industry to increase the productivity of wells in reservoirs with a small thickness. Drilling these wells has been a challenge due to the low rate of penetration (ROP) and severe wellbore instability issues. The objective of this research is to reach a better drilling performance by reducing drilling time and increasing wellbore stability.
In this work, the first step was to develop a model that predicts the ROP for deviated wells by applying Artificial Neural Networks (ANNs). In the modeling, azimuth (AZI) and inclination (INC) of the wellbore trajectory, controllable drilling parameters, unconfined compressive strength (UCS), formation
... Show MoreDrilling deviated wells is a frequently used approach in the oil and gas industry to increase the productivity of wells in reservoirs with a small thickness. Drilling these wells has been a challenge due to the low rate of penetration (ROP) and severe wellbore instability issues. The objective of this research is to reach a better drilling performance by reducing drilling time and increasing wellbore stability.
In this work, the first step was to develop a model that predicts the ROP for deviated wells by applying Artificial Neural Networks (ANNs). In the modeling, azimuth (AZI) and inclination (INC) of the wellbore trajectory, controllable drilling parameters, unconfined compressive strength (UCS), formation
... Show MoreNow that most of the conventional reservoirs are being depleted at a rapid pace, the focus is on unconventional reservoirs like tight gas reservoirs. Due to the heterogeneous nature and low permeability of unconventional reservoirs, they require a huge number of wells to hit all the isolated hydrocarbon zones. Infill drilling is one of the most common and effective methods of increasing the recovery, by reducing the well spacing and increasing the sweep efficiency. However, the problem with drilling such a large number of wells is the determination of the optimum location for each well that ensures minimum interference between wells, and accelerates the recovery from the field. Detail