Optical Mark Recognition (OMR) is an important technology for applications that require speedy, high-accuracy processing of a huge volume of hand-filled forms. The aim of this technology is to reduce manual work, human effort, high accuracy in assessment, and minimize time for evaluation answer sheets. This paper proposed OMR by using Modify Bidirectional Associative Memory (MBAM), MBAM has two phases (learning and analysis phases), it will learn on the answer sheets that contain the correct answers by giving its own code that represents the number of correct answers, then detection marks from answer sheets by using analysis phase. This proposal will be able to detect no selection or select more than one choice, in addition, using M

The manual classification of oranges according to their ripeness or flavor takes a long time; furthermore, the classification of ripeness or sweetness by the intensity of the fruit’s color is not uniform between fruit varieties. Sweetness and color are important factors in evaluating the fruits, the fruit’s color may affect the perception of its sweetness. This article aims to study the possibility of predicting the sweetness of orange fruits based on artificial intelligence technology by studying the relationship between the RGB values of orange fruits and the sweetness of those fruits by using the Orange data mining tool. The experiment has applied machine learning algorithms to an orange fruit image dataset and performed a co

The trade war, of course, leads to a sharp tension in international relations because the economy is the lifeblood of the states. In the world of trade and economy, countries began to lean towards cooperation. Economic relations after World War II were more liberal, trade barriers were removed and global trade became more flexible and smooth

This research aims to explore the status effects of the Sudden, and gradual of AI-Driven Cyber Security (AIDC), Big data analytics and Business Intelligence (BI) The strategic flexibility (SF) and entrepreneurship (ENT) on Iraqi internet services providers ISPs. The work fills an important lacunae in what the advanced dimensions of technology have with regard to its influencing both SF and ENT outcomes in developing economy context, where empirical evidences are scant. A cross-sectional survey based on a quantitative research methodology was conducted on 113 professionals in Iraqi telecommunication sector. A partial least squares structural equation modeling (PLS-SEM) approach was adopted to examine 10 hypotheses concerning the relationship

Background: Laparoscopic cholecystectomy has many difficulties which include port Insertion, Dissectionof the Calot’s Triangle , Grasping of the Gallbladder , Wall thickness, Adhesion and extraction of theGallbladder. Aim of the Study: To predict how difficult cholecystectomy will be from assessing the patientpreoperatively which, in turn, help in decreasing the risks on the patients and preventing post-operativecomplications. Patients and Methods: A prospective study conducted in the department of General Surgeryat Al-Ramadi Teaching Hospital for the period of nine months from 15th of May 2018 till the 15th of February2019. It included 60 patients, all of them were undergone laparoscopic cholecystectomy for Gallstone. Patientswit

The aim of this study is to investigate the protective effect of Radish (Raphanus sativus) seed alcoholic extract 70% against oxidative stress induced by sodium nitrite NaNO2 Twenty five adult male rabbits were devided into five groups of (five rabbits in each group) and treated daily for 30 days. Group T1: intubated orally 20 mg/kg NaNO2, Group T2: intubated orally 20 mg/kg NaNO2 + 50 mg/kg of alcoholic extract from Raphanus sativus seeds, Group T3: intubated orally 20 mg/kg NaNO2 + 100 mg/kg of alcoholic extract from Raphanus sativus seeds, Group T4: intubated orally 20 mg/kg NaNO2 + 200 mg/kg of alcoholic extract from Raphanus sativus seed as well as Group C: control intubated orally distilled water. In comparison with normal ra

Abstract

  Bivariate time series modeling and forecasting have become a promising field of applied studies in recent times. For this purpose, the Linear Autoregressive Moving Average with exogenous variable ARMAX model is the most widely used technique over the past few years in modeling and forecasting this type of data. The most important assumptions of this model are linearity and homogenous for random error variance of the appropriate model. In practice, these two assumptions are often violated, so the Generalized Autoregressive Conditional Heteroscedasticity (ARCH) and (GARCH) with exogenous varia