This research aims to analyze and simulate biochemical real test data for uncovering the relationships among the tests, and how each of them impacts others. The data were acquired from Iraqi private biochemical laboratory. However, these data have many dimensions with a high rate of null values, and big patient numbers. Then, several experiments have been applied on these data beginning with unsupervised techniques such as hierarchical clustering, and k-means, but the results were not clear. Then the preprocessing step performed, to make the dataset analyzable by supervised techniques such as Linear Discriminant Analysis (LDA), Classification And Regression Tree (CART), Logistic Regression (LR), K-Nearest Neighbor (K-NN), Naïve Bays (NB

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

Analyzing sentiment and emotions in Arabic texts on social networking sites has gained wide interest from researchers. It has been an active research topic in recent years due to its importance in analyzing reviewers' opinions. The Iraqi dialect is one of the Arabic dialects used in social networking sites, characterized by its complexity and, therefore, the difficulty of analyzing sentiment. This work presents a hybrid deep learning model consisting of a Convolution Neural Network (CNN) and the Gated Recurrent Units (GRU) to analyze sentiment and emotions in Iraqi texts. Three Iraqi datasets (Iraqi Arab Emotions Data Set (IAEDS), Annotated Corpus of Mesopotamian-Iraqi Dialect (ACMID), and Iraqi Arabic Dataset (IAD)) col

Sentiment analysis is one of the major fields in natural language processing whose main task is to extract sentiments, opinions, attitudes, and emotions from a subjective text. And for its importance in decision making and in people's trust with reviews on web sites, there are many academic researches to address sentiment analysis problems. Deep Learning (DL) is a powerful Machine Learning (ML) technique that has emerged with its ability of feature representation and differentiating data, leading to state-of-the-art prediction results. In recent years, DL has been widely used in sentiment analysis, however, there is scarce in its implementation in the Arabic language field. Most of the previous researches address other l

Porosity and permeability are the most difficult properties to determine in subsurface reservoir characterization. The difficulty of estimating them arising from the fact that porosity and permeability may vary significantly over the reservoir volume, and can only be sampled at well location. Secondly, the porosity values are commonly evaluated from the well log data, which are usually available from most wells in the reservoir, but permeability values, which are generally determined from core analysis, are not usually available. The aim of this study is: First, to develop correlations between the core and the well log data which can be used to estimate permeability in uncored wells, these correlations enable to estimate reservoir permeabil

Polyphenol oxidase (PPO) is an enzyme containing copper, presents in various fruits and vegetables. It is responsible for the browning reactions when the cells are damaged during handling. The best conditions for extraction of polyphenol oxidase from banana peel was by using an extraction buffer containing phosphate buffer (0.05 M, pH 7), 0.01 M ascorbic acid and 0.5% polyethylene glycol, with extraction ratio 1:4 (w:v) for one minute by using blender. The enzyme activity was measured spectrophotometrically at 425 nm. PPO was studied to prevent the browning of banana peel which results in the loss of their marketability. The aim of this study was to determine the optimum conditions for polyphenol oxidase extraction from banana peel.

Purpose/objective:

1 - To explain the financial impact of the activities and areas of human resources management and the adoption of the methodology for estimating costs on the basis of conduct and statement of how to assess costs and benefits of human resource activities.

2 - Measuring  human capital, and its impact on the financial statements.

Design/methodology/approach:

 Concentrated dimensions of the research paper's lack of financial statements prepared by the organizations for information mandated human resource its components of the three (attraction - development

The ability of pulverized walnut-shell to remove oil from aqueous solutions has been studied. It involves two-phase process which consists of using walnut-shell as a filtering bed for the accumulation and adsorption of oil onto its surface. Up to 96% oil removal from synthetic wastewater samples was achieved while tests results showed that 75% of oil can be removed from the actual wastewater discharged from Al- Duara refinery in the south of Baghdad.