With its rapid spread, the coronavirus infection shocked the world and had a huge effect on billions of peoples' lives. The problem is to find a safe method to diagnose the infections with fewer casualties. It has been shown that X-Ray images are an important method for the identification, quantification, and monitoring of diseases. Deep learning algorithms can be utilized to help analyze potentially huge numbers of X-Ray examinations. This research conducted a retrospective multi-test analysis system to detect suspicious COVID-19 performance, and use of chest X-Ray features to assess the progress of the illness in each patient, resulting in a "corona score." where the results were satisfactory compared to the benchmarked techniques.  T

In this paper, we will provide a proposed method to estimate missing values for the Explanatory variables for Non-Parametric Multiple Regression Model and compare it with the Imputation Arithmetic mean Method, The basis of the idea of this method was based on how to employ the causal relationship between the variables in finding an efficient estimate of the missing value, we rely on the use of the Kernel estimate by Nadaraya – Watson Estimator , and on Least Squared Cross Validation (LSCV) to estimate the Bandwidth, and we use the simulation study to compare between the two methods.

The water injection of the most important technologies to increase oil production from petroleum reservoirs. In this research, we developed a model for oil tank using the software RUBIS for reservoir simulation. This model was used to make comparison in the production of oil and the reservoir pressure for two case studies where the water was not injected in the first case study but adding new vertical wells while, later, it was injected in the second case study. It represents the results of this work that if the water is not injected, the reservoir model that has been upgraded can produce only 2.9% of the original oil in the tank. This case study also represents a drop in reservoir pressure, which was not enough to support oil production

The core objective of this paper was to diagnosis and detect the expected rotor faults in small wind turbine SWT utilize signal processing technique. This aim was achieved by acquired and analyzed the current signal of SWT motor and employed the motor current signature analysis MCSA to detect the sudden changes can have occurred during SWT operation. LabVIEW program as a virtual instrument and (NI USB 6259) DAQ were take advantage of current measurement and data processing.

Topic management is the awareness of how speakers deal with initiating, developing, changing, and ending a topic and how they fix the relationship when a misunderstanding occurs. It is such an important unit of conversation as it includes the transition from one strategy to the other to be accomplished in a systematic and orderly manner. These strategies are impaired in dementia patients thus lead to communication breakdown. This study aims at detecting the dementia patients' topic management strategies in selected speeches and answering the questions of which of these strategies are fully or partially detected in these speeches. The researchers use a qualitative method to examine the speeches of those patients and they adopt an eclectic

The advancement of digital technology has increased the deployment of wireless sensor networks (WSNs) in our daily life. However, locating sensor nodes is a challenging task in WSNs. Sensing data without an accurate location is worthless, especially in critical applications. The pioneering technique in range-free localization schemes is a sequential Monte Carlo (SMC) method, which utilizes network connectivity to estimate sensor location without additional hardware. This study presents a comprehensive survey of state-of-the-art SMC localization schemes. We present the schemes as a thematic taxonomy of localization operation in SMC. Moreover, the critical characteristics of each existing scheme are analyzed to identify its advantages

The research aims to evaluate the suppliers at Diyala general electric industries company conducted in an environment of uncertainty and fuzzy where there is no particular system followed by the company, and also aims to use the problem of traveling salesman problem in the process of transporting raw materials from suppliers to the company in a fuzzy environment. Therefore, a system based on mathematical methods and quantity was developed to evaluate the suppliers. Fuzzy inference system (FIS) and fuzzy set theory were used to solve this problem through (Matlab) and the problem of the traveling salesman in two stages was also solved by the first stage of eliminating the fuzzing of the environment using the rank function method, w

“Smart city” projects have become fully developed and are actively using video analytics. Our study looks at how video analytics from surveillance cameras can help manage urban areas, making the environment safer and residents happier. Every year hundreds of people fall on subway and railway lines. The causes of these accidents include crowding, fights, sudden health problems such as dizziness or heart attacks, as well as those who intentionally jump in front of trains. These accidents may not cause deaths, but they cause delays for tens of thousands of passengers. Sometimes passers-by have time to react to the event and try to prevent it, or contact station personnel, but computers can react faster in such situations by using ethical

A numerical investigation of mixed convection in a horizontal annulus filled with auniform fluid-saturated porous medium in the presence of internal heat generation is carried out.The inner cylinder is heated while the outer cylinder is cooled. The forced flow is induced by thecold outer cylinder rotating at a constant angular velocity. The flow field is modeled using ageneralized form of the momentum equation that accounts for the presence of porous mediumviscous, Darcian and inertial effects. Discretization of the governing equations is achieved usinga finite difference method. Comparisons with previous works are performed and the results showgood agreement. The effects of pertinent parameters such as the Richardson number and internalRay

Background: Prolactin is a hormone, as well as a cytokine which is synthesized and secreted from the anterior pituitary gland and various extra pituitary sites including immune cells under control of a superdistal promoter that contains a single nucleotide polymorphism -1149 G/T. Rheumatoid Arthritis has been associated with increased serum prolactin levels.Objectives: To investigate the association of the extra pituitary -1149 G/T promoter polymorphism among Iraqi rheumatoid arthritis patients and prolactin levels.Methods: We tested 73 patients with rheumatoid arthritis and 40 healthy individuals. The DNA samples were genotyped using the Polymerase Chain Reaction-Restriction fragment Length Polymorphism method and the levels of prolacti