Many academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Decision Trees (DT), K- nearest neighbor (KNN), and Logistic Regression (LR), have been used to identify the parameters that allow for effective price estimation. These approaches were tested on a data set of an extensive Indian airline network. When it came to estimating flight prices, the results demonstrate that the Decision tree method is the best conceivable Algorithm for predicting the price of a flight in our particular situation with 89% accuracy. The SGD method had the lowest accuracy, which was 38 %, while the accuracies of the KNN, NB, ADA, and LR algorithms were 69 %, 45 %, and 43 %, respectively. This study's presented methodologies will allow airline firms to predict flight prices more accurately, enhance air travel, and eliminate delay dispersion.
Diagnosing heart disease has become a very important topic for researchers specializing in artificial intelligence, because intelligence is involved in most diseases, especially after the Corona pandemic, which forced the world to turn to intelligence. Therefore, the basic idea in this research was to shed light on the diagnosis of heart diseases by relying on deep learning of a pre-trained model (Efficient b3) under the premise of using the electrical signals of the electrocardiogram and resample the signal in order to introduce it to the neural network with only trimming processing operations because it is an electrical signal whose parameters cannot be changed. The data set (China Physiological Signal Challenge -cspsc2018) was ad
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Abstract
Objective(s): To evaluate blended learning in nursing education at the Middle Region in Iraq.
Methodology: A descriptive study, using evaluation approach, is conducted to evaluate blended learning in nursing education in Middle Region in Iraq from September 26th, 2021 to March 22nd, 2022. The study is carried out at two Colleges of Nursing at the University of Baghdad and University of Tikrit in Iraq. A convenient, non-probability, sample of (60) undergraduate nursing students is selected. The sample is comprised of (30) student from each college of nursing, Self-report questionnaire is constructed from the literature, for e
... Show MoreThe study aims at identifying the sources of information and explaining their role in e-learning from the viewpoint of the Iraqi college students. The researchers relied on the descriptive method of the survey method to collect data and know the point of view of undergraduate students from the Department of Information in the College of Arts / Tikrit University and the Department of Quranic Studies at the College of Arts / University of Baghdad. The questionnaire was used as an instrument of the study, the research sample is (120) students; each section has (60) male and female students. The study concluded that there are many types and forms of information sources that students receive through electronic educational platforms from text con
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ABSTRACT
Learning vocabulary is a challenging task for female English as a foreign language (EFL) students. Thus, improving students’ knowledge of vocabulary is critical if they are to make progress in learning a new language. The current study aimed at exploring the vocabulary learning strategies used by EFL students at Northern Border University (NBU). It also aimed to identify the mechanisms applied by EFL students at NBU University to learn vocabulary. It also aimed at evaluating the approaches adopted by EFL female students at Northern Border University (NBU) to learn a language. The study adopted the descriptive-analytical method. Two research instruments were developed to collect data namely, a survey qu
... Show MoreA Wearable Robotic Knee (WRK) is a mobile device designed to assist disabled individuals in moving freely in undefined environments without external support. An advanced controller is required to track the output trajectory of a WRK device in order to resolve uncertainties that are caused by modeling errors and external disturbances. During the performance of a task, disturbances are caused by changes in the external load and dynamic work conditions, such as by holding weights while performing the task. The aim of this study is to address these issues and enhance the performance of the output trajectory tracking goal using an adaptive robust controller based on the Radial Basis Function (RBF) Neural Network (NN) system and Hamilton
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The A2?u-X1?g+ emission band system of 7LiH1 molecule has been calculated for Lambda doubling. The relation between wave number ?p , ?Q , ?R conducted the energies of the state of rotation F (J), and (J + 1) with rotational quantum number J, respectively, of 7LiH1 molecule for statehood A2?u using the rotation, fixed vibrational states of both the ground and raised crossovers vibrational against ???= 0 to V ' = 0-4using rotational levels J = 0 to J = 20 have found.
This paper proposes a novel method for generating True Random Numbers (TRNs) using electromechanical switches. The proposed generator is implemented using an FPGA board. The system utilizes the phenomenon of electromechanical switch bounce to produce a randomly fluctuated signal that is used to trigger a counter to generate a binary random number. Compared to other true random number generation methods, the proposed approach features a high degree of randomness using a simple circuit that can be easily built using off-the-shelf components. The proposed system is implemented using a commercial relay circuit connected to an FPGA board that is used to process and record the generated random sequences. Applying statistical testing on th
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In this paper, an enhanced artificial potential field (EAPF) planner is introduced. This planner is proposed to rapidly find online solutions for the mobile robot path planning problems, when the underlying environment contains obstacles with unknown locations and sizes. The classical artificial potential field represents both the repulsive force due to the detected obstacle and the attractive force due to the target. These forces can be considered as the primary directional indicator for the mobile robot. However, the classical artificial potential field has many drawbacks. So, we suggest two secondary forces which are called the midpoint
... Show MoreReverse osmosis membrane desalination is one of the most significant water treatments that is used to offer freshwater. The aim of this research is to study the effect of controlling the value of the zeta potential on the suspended particles in the water and the proximity of the membrane surfaces in the colloidal solution, to keep the water stable electrically and disperse the colloidal particles. To achieve this aim, the experimental study was conducted in the Sanitary Engineering Laboratory, in the engineering college - University of Baghdad. Two systems were set up, one worked normally and the other worked by using the zeta rod placed before the reverse osmosis membrane. The results showed that the effect of the zeta rod increas
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