Big data analysis has important applications in many areas such as sensor networks and connected healthcare. High volume and velocity of big data bring many challenges to data analysis. One possible solution is to summarize the data and provides a manageable data structure to hold a scalable summarization of data for efficient and effective analysis. This research extends our previous work on developing an effective technique to create, organize, access, and maintain summarization of big data and develops algorithms for Bayes classification and entropy discretization of large data sets using the multi-resolution data summarization structure. Bayes classification and data discretization play essential roles in many learning algorithms such a

<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol

<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol

Objective; swine flu is known to be caused by influenza A subtypes H1N1,H1N2, H2N3, H3N1, and H3N2, was first proposed to be a disease related to human flu during the 1918 flu pandemic, Iraq face the epidemic of 2009, many patients admitted to the medical word of alkindy teaching hospital, the clinical features were observed and managed according to WHO protocols.
The aim of the study; is to asses some features of morbidity and mortality of swine flu epidemic admitted patients in 2009 in alkindy teaching hospital.
Methods; A total 131 patients with suspected influenza
admitted to Alkindy Teaching Hospital all complain of
fever more than 38c, sore throat with or without cough.
The admitted patients are of two main
groups

Objective; swine flu is known to be caused by influenza A subtypes H1N1,H1N2, H2N3, H3N1, and H3N2, was first proposed to be a disease related to human flu during the 1918 flu pandemic, Iraq face the epidemic of 2009, many patients admitted to the medical word of alkindy teaching hospital, the clinical features were observed and managed according to WHO protocols.
The aim of the study; is to asses some features of morbidity and mortality of swine flu epidemic admitted patients in 2009 in alkindy teaching hospital.
Methods; A total 131 patients with suspected influenza
admitted to Alkindy Teaching Hospital all complain of
fever more than 38c, sore throat with or without cough.
The admitted patients are of two main
groups

The study investigates the relationship between the volatility of the Iraqi Stock Exchange Index (ISX), and the volatility of global oil prices benchmarks, Brent and West Intermediate Texas (WTI), in additional to the Iraqi Oil, Basra Crude Light (BSL) which represents the most exported Iraqi oil and the major influential factor on the Iraqi governmental revenues. Using monthly data covering the period: 1/2005-12/1205, econometrical and technical tools represented by Co-incretion, Vector Error Correction Model – VECM, Granger Causality, and Bollinger band were employed in order to explore the relationship between the variables.

The econometric analysis revealed the impact of the oil prices volatility on

The goal of the research is to highlight the role of the governance and its characteristics in increasing the tax outcome by implementing the laws, regulations and annual controls issued annually from the general authority for taxation for the financing of the general treasury of the state, Additional development and economic capacity, As the search shares a view of the governance and its characteristics and its ideas from increasing tax output. The analytical transparent approach was used by adopting the practice of practicalities of the general authority for tax For quotations in the senior cabinet section ,the revealing of the ongoing operations was relied on the revenue for each financial year, The tools adopted in the process of ana

Evaluate the acute and chronic toxicity of Ruta Chalepensis aerial part aqueous extract used in folk medicine in Iraq in Albino Wistar male and female rats. The study of chronic toxicity at the doses 100, 300 and 600mg/kg body weight in male and female rats for 90 days, recorded no mortality. Treated animals showed a normal weight change compared with control. The parameters of male fertility showed a significant decrease in the weight of testis, epididymis and seminal vesicle as well as a reduction in the number and the motility of spermatozoids at treated groups by the doses 300 and 600 mg/kg body weight compared to control group.

At the end of 2019, a new form of Coronavirus (later dubbed COVID-19) emerged in China and quickly spread to other regions of the globe. Despite the virus’s unique and unknown characteristics, it is a widely distributed infectious illness. Finding the geographical distribution of the virus transmission is therefore critical for epidemiologists and governments in order to respond to the illness epidemic rapidly and effectively. Understanding the dynamics of COVID-19’s spatial distribution can help to understand the pandemic’s scope and effects, as well as decision-making, planning, and community action aimed at preventing transmission. The main focus of this study is to investigate the geographic patterns of COVID-19 disseminat